Jobs — Data Scientists

Manager, Machine Learning Engineering - Ad Platforms

The Walt Disney Company · Seattle, WA

Manager Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's or master's degree in computer science, Engineering,
Mathematics, Statistics, or a related field.
8+ years of relevant industry experience, with at least 2-3 years in a people-management or technical leadership role.
Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
Proven experience designing, building, and deploying scalable machine learning models and systems in production.
Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
Demonstrated ability to lead global teams and collaborate across organizational boundaries.

Preferred

Domain knowledge in the Ad Tech industry
Experience working with large-scale data and distributed systems.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
The hiring range for this position in Los Angeles, CA area is $171,600 - $230,100 per year and Seattle Area is $179,700 - $241,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
*Job ID: 10152782

Responsibilities

You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
Daily, you should bring:
A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
A passion for mentoring, learning, and taking on new challenges.
A proven ability to work with product teams to translate requirements into
well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
A keen eye for potential optimizations and enhancements.
Kindness and pragmatic optimism.
A deep understanding of model development cycles and AI tool usage
Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
Drive adoption of best practices in model development, code quality, testing, and documentation.
Solid understanding and usage of automated tools (AI) while adhering to company policy.
Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
Foster innovation by exploring new ML techniques, tools, and technologies.
Communicate strategies, progress, and results to leadership and cross-functional teams.
Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions

View full posting on CareerOneStop → ID: 0f8ff097436c

Senior Machine Learning Engineering Manager, Ad Platforms

The Walt Disney Company · Seattle, WA

Manager Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field.
10+ years of relevant industry experience, with at least 5 years in people-management managing senior ICs and managers.
Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
Proven experience designing, building, and deploying scalable machine learning models and systems in production.
Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
Demonstrated ability to lead global teams and collaborate across organizational boundaries.

Preferred

Domain knowledge in the Ad Tech industry
Experience working with large-scale data and distributed systems.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
The hiring range for this position in Los Angeles, CA area is $207,400 - $278,100 per year and Seattle Area is $217,300 - $291,500. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
*Job ID: 10152780

Responsibilities

You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
Daily, you should bring:
A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
A passion for mentoring, learning, and taking on new challenges.
A proven ability to work with product teams to translate requirements into
well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
A keen eye for potential optimizations and enhancements.
Kindness and pragmatic optimism.
A deep understanding of model development cycles and AI tool usage
Lead, mentor and guide senior individual contributors and managers across data scientists, machine learning and AI engineers teams to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
Drive adoption of best practices in model development, code quality, testing, and documentation.
Solid understanding and usage of automated tools (AI) while adhering to company policy.
Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
Foster innovation by exploring new ML techniques, tools, and technologies.
Communicate strategies, progress, and results to leadership and cross-functional teams.
Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions

View full posting on CareerOneStop → ID: f33cab28b6a2

Data Scientist, Technology Consulting, AI & Data, Government & Public Sector (Manager)(Multiple Posi

EY Government Services LLC · Seattle, WA

Manager

2026-06-04

WA 2026-06-04

View full posting on CareerOneStop → ID: f6fcb6c1a380

Machine Learning Engineering Manager

Indeed · Seattle, WA

Manager Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 85c5b878e3fc

Machine Learning Engineering Manager

Indeed · Portland, OR

Manager Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 1dab31464fa0

Machine Learning Engineering Manager

Indeed · Boise, ID

Manager Doctorate

2026-06-03

ID 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: fa90c2d42649

Machine Learning Engineering Manager

Indeed · Helena, MT

Manager Doctorate

2026-06-03

MT 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 86c5ccbc5a93

Technical Project Manager - Machine Learning & Data Science

Cadmus · Olympia, WA

Manager Bachelor's

2026-05-30

WA 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 9a2c5d789c8e

Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)

Amazon · Seattle, WA

Manager Master's

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
5+ years of finance or a related analytical field experience
Experience coordinating between technical teams, peers and business stakeholders
5+ years of experience creating financial models and strategic analyses that support business decisions

Preferred

Experience in TM1, Data Warehouse and SQL
Experience with AI/ML technologies
Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
Advertising or Media experience is a plus

Responsibilities

Business Partnering & Performance Management
Serve as the finance partner for Performance Measurement and Infrastructure leadership
Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
Support monthly business reviews with insights, variance analysis, and recommendations
Strategic Analysis & Cost Management
Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
Deliver analyses that translate complex technical problems into actionable insights for senior leadership
Partner with BIE and analytics teams to build scalable dashboards and automated reporting
Cross-Functional Collaboration & Operational Excellence
Partner with product, engineering, data science, and sales teams to align strategy with business priorities
Collaborate across Advertising Finance to ensure consistency in planning and reporting
Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo

View full posting on CareerOneStop → ID: e9237370ca84

Technical Project Manager - Machine Learning & Data Science

Cadmus · Boise, ID

Manager Bachelor's

2026-05-30

ID 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 6009b75ef456

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salem, OR

Manager Bachelor's

2026-05-30

OR 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: a610d659809f

Technical Project Manager - Machine Learning & Data Science

Cadmus · Helena, MT

Manager Bachelor's

2026-05-30

MT 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: e8819b62977f

Manager - Data Science / Data Lake

Deloitte · Seattle, WA

Manager Bachelor's

2026-05-29

WA 2026-05-29

Requirements

10+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these
10+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
10+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
Experience working with cyber security cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a field aligned to the role; or 4 years of equivalent professional experience
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred

Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response acceleration
Experience parsing and normalizing cyber or information technology telemetry datasets
Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Experience with Apache Kafka, Storm, or Spark
Experience creating client-ready materials using Microsoft PowerPoint or Microsoft Visio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 6e0e84031d18

Senior Product Data Scientist Manager, Android

Google · Kirkland, WA

Manager Master's

2026-05-27

WA 2026-05-27

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
13 years of work experience using analytics to solv.e product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience and a Master's degree)
5 years of experience as a people manager within a technical leadership role.

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
6 years of experience as a people manager within a technical leadership role.

Responsibilities

Android, Business, and Communications (ABC) is at the core of how people and businesses connect across the globe. Our mission is to build the world's most helpful, expressive, and secure communication experiences. With communication apps such as Google Messages and Dialer, we ship products that make a meaningful difference in billions of lives worldwide.
We define standard-setting "toothbrush journeys"-from fundamental calling reliability to high-resolution media sharing and expressive reactions. Beyond peer-to-peer connection, we are pioneering the next generation of conversational commerce, enabling businesses to deliver app-like experiences directly within the messaging interface. Whether adapting mobile features for a multi-device world on Wear OS or driving engagement with features like call screen, we focus on high-impact innovation that connects everyone, regardless of their device.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
The US base salary range for this full-time position is $240,000-$334,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
Own projects end-to-end, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.
Address ambiguous or new problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
Lead a team of data scientists, oversee technical accuracy across the organization, provide essential technical oversight for ranking, personalization, and classification strategies to scale the business globally.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: c1b62ce0b414

Data Science Manager, Gen AI - SFL Scientific

Deloitte · Seattle, WA

Manager Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
6+ years of experience working in data science, data engineering, software engineering, or MLOps
6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
4+ years of experience managing teams and delivering complex and critical projects
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
Experience with developing and testing GenAI solutions
Experience in a client-facing role or internal AI product development role
Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: b49278c50cf0

Data Science Manager, Gen AI - SFL Scientific

Deloitte · Portland, OR

Manager Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
6+ years of experience working in data science, data engineering, software engineering, or MLOps
6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
4+ years of experience managing teams and delivering complex and critical projects
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
Experience with developing and testing GenAI solutions
Experience in a client-facing role or internal AI product development role
Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 51a9883c9b6b

Data Science Manager, PXT Central Science

Amazon · Seattle, WA

Manager Master's

2026-05-22

WA 2026-05-22

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions

View full posting on CareerOneStop → ID: 343cbeff7e60

Data Science Manager, PXT Central Science

Amazon · Bellevue, WA

Manager Master's

2026-05-22

WA 2026-05-22

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions

View full posting on CareerOneStop → ID: c4a3c0ed4ac4

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Seattle, WA

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: d4ce7ce958d6

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Olympia, WA

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: 4f65551cb8e5

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Portland, OR

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: 06cb3337d70e

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Salem, OR

Manager Doctorate

2026-05-21

OR 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: cd7c9bd89325

Senior Manager, Data Science and Analytics, Prime Video Personalization & Analytics

Amazon · Seattle, WA

Manager

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 5f7a59868129

Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)

Amazon · Seattle, WA

Manager Master's

2026-05-20

WA 2026-05-20

Requirements

Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
5+ years of finance or a related analytical field experience
Experience coordinating between technical teams, peers and business stakeholders
5+ years of experience creating financial models and strategic analyses that support business decisions

Preferred

Experience in TM1, Data Warehouse and SQL
Experience with AI/ML technologies
Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
Advertising or Media experience is a plus

Responsibilities

Business Partnering & Performance Management
Serve as the finance partner for Performance Measurement and Infrastructure leadership
Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
Support monthly business reviews with insights, variance analysis, and recommendations
Strategic Analysis & Cost Management
Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
Deliver analyses that translate complex technical problems into actionable insights for senior leadership
Partner with BIE and analytics teams to build scalable dashboards and automated reporting
Cross-Functional Collaboration & Operational Excellence
Partner with product, engineering, data science, and sales teams to align strategy with business priorities
Collaborate across Advertising Finance to ensure consistency in planning and reporting
Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo

View full posting on CareerOneStop → ID: 0c166170a6d9

Principal Product Manager, Data Science

Norstella · Olympia, WA

Manager Master's

2026-05-20

WA 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 352068afaa9f

Principal Product Manager, Data Science

Norstella · Boise, ID

Manager Master's

2026-05-20

ID 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 0925bd9bfd98

Principal Product Manager, Data Science

Norstella · Salem, OR

Manager Master's

2026-05-20

OR 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 04cc7306bca0

Principal Product Manager, Data Science

Norstella · Helena, MT

Manager

2026-05-20

MT 2026-05-20

View full posting on CareerOneStop → ID: 4db43b0a5f50

Technical Program Manager II, Data Center Planning, Machine Learning

Google · Kirkland, WA

Manager Bachelor's

2026-05-16

WA 2026-05-16

Requirements

Bachelor's degree in a technical field, or equivalent practical experience.
2 years of experience in program management.
Experience in one of the following planning areas (e.g., capacity planning, supply planning, demand planning, or data center planning).
Experience in data modeling and analysis.

Preferred

5 years of experience in capacity planning, strategic operations planning, data analytics, inventory optimization, or management/operations consulting.
2 years of experience managing cross-functional or cross-team projects.
Experience collaborating and influencing stakeholders spanning across multiple organizations and different levels of responsibilities.
Demonstrated ability to take complex, ambiguous topics and create compelling narratives and present them to leadership.
Ability to shift between direct detailed analysis and big picture thinking and customizing communication based on the audience.
Excellent data analysis skills (e.g., Sheets, SQL).

Responsibilities

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
The Data Center Planning organization is responsible for identifying the most cost-efficient set of data centers to meet a 5-year forecast demand signal and for identifying and planning the Product Areas (PAs) who will occupy them. We drive alignment on what we should build, where, when, and who may occupy it through the Building Demand Plan (BDP) and Earmarks, an extensive set of optimization processes which provides demand justification and outlook for capital funding of data centers. This in turn provides signals to the downstream partner teams to identify new supply options and expansion of current facilities and assets. Within DCP, the Demand and Allocation Planning team is responsible for developing and maintaining our end-to-end power plan of record and continuously seeking to deliver further optimization through extensive scenario planning. We provide key upstream and downstream partners with chase signals, driving the acquisition of additional capacity, configuration of facilities to support the latest ML chips, and even where we may need to shape demand between geographies.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Offer clear, concise, and logical judgment and actionable recommendations to partners and executives in a timely manner regarding Google's data center capacity needs.
Use data to identify planning solutions and provide advice to business leaders across the organization.
Codify, maintain, and update Google PAs' technical and business requirements in partnership with Product Area Resource Managers (PARMs), and use them to influence execution and Google's spend and capacity allocation decisions.
Implement new DC power planning initiatives, including automation with engineering support and cross-functional policy changes.
Work with the customer to manage and resolve all DC capacity related issues and escalations.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 19e4e76090b4

Technical Program Manager III, Machine Learning, Google Cloud

Google · Kirkland, WA

Manager Doctorate

2026-05-16

WA 2026-05-16

Requirements

Bachelor's degree in a relevant field, or equivalent practical experience.
5 years of experience in program management.
Experience working with data structures or machine learning algorithms.

Preferred

Master's degree, PhD, or equivalent experience in Engineering, Computer Science, or other technical related field.
5 years of experience managing cross-functional or cross-team projects.
3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, or deep learning.

Responsibilities

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
Using your extensive technical and leadership expertise, you'll manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Provide software development and project management, coordination, and inter/intra team communications to deliver outstanding program outcomes.
Work closely with Software Engineers, QA, Product Managers and other engineering teams to get high-quality products and features through the software project lifecycle (build, test and release on time).
Manage project schedules, identify possible issues and clearly communicate them to project stakeholders.
Lead several technical programs for Google Cloud, setting priorities for products and engineering, leading teams to take products to market, assuring success metrics are informing future efforts, and quickly fine tuning the program as needed.
Exercise knowledge of data structures or algorithms that improve software performance over time. Build, maintain and enhance business, operational, and management dashboards
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 87cede07c68e

Data Science Manager

Maximus · Boise, ID

Manager Bachelor's

2026-05-15

ID 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: be3e4ab14d9d

Data Science Manager

Maximus · Salem, OR

Manager Bachelor's

2026-05-15

OR 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: ce74020e7d03

Data Science Manager

Maximus · Olympia, WA

Manager Bachelor's

2026-05-15

WA 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: 30584effbdd7

Data Science Manager

Maximus · Helena, MT

Manager

2026-05-15

MT 2026-05-15

View full posting on CareerOneStop → ID: 8d1a0cfa10ff

Senior Machine Learning Manager, Search & Knowledge Platform

Apple · Seattle, WA

Manager Doctorate

2026-05-13

WA 2026-05-13

Requirements

8+ years of experience in leading engineering/applied research/ML experiences in natural language processing, SOTA generative AI models
Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field

Preferred

Strong background and experience in Machine Learning, NLP, and RAG.
Strong engineering and R&D experience in LLM post-training, advanced RL-based methods to improve LLM models' safety and quality using RLHF/RLAIF, reward model, advanced RL policy optimization algorithms, cutting-edge hallucination reduction methods, and their engineering implementation, hands-on experience to develop and ship RL based models with high availability, low latency, robustness, and stability.
Exceptional verbal and written communication skills to lead
Excellent product vision and sound business acumen. Ability to manage long-term strategy and short-term deliverables.
Strong engineering leadership and fundamentals.

Responsibilities

Apple is where individual imaginations gather together, contributing to the values that lead to great work. Every The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient and effective Generative AI models to build and improve the summarization capabilities across different data types.
In this role, you'll drive E2E R&D and engineering to generate high-quality summaries and experiences for Apple users. This includes on-device LLM models for personal content summarization across 1P and 3P apps, and powerful summarization models on Apple's Private Cloud Compute servers. In addition, improve the summarization models' quality for world knowledge-seeking questions and Safari pages to provide accurate answers and highlight web page gists in real-time. Lead the team to develop SOTA LLM-based generative models, groundedness models, and safety models for accurate, grounded, concise, and safe summaries. Develop sophisticated on-device and on-server software frameworks for context integration fast and cost-efficient LLM-based model inference. Integrate the Apple ecosystem with Apple's LLM infrastructure and generative models to deliver delightful user experiences. Devise the product vision and strategy and execute the plan to deliver the highest quality end-user experience. Collaborate with various organizational partners to profoundly impact billions of Apple users worldwide.

View full posting on CareerOneStop → ID: 01ef76150873

Senior Machine Learning Manager, Search & Knowledge Platform

Apple · Santa Clara, CA

Manager

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: c39885d38bac

Sr. Manager , Annapurna Labs - Cloud Scale Machine Learning Acceleration Team

Amazon · Tempe, AZ

Manager

2026-05-13

AZ 2026-05-13

View full posting on CareerOneStop → ID: 5c0c1505aed5

Manager & Senior Data Scientist

Travelers Insurance Company · Saint Paul, MN

Manager

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: 859a493979c3

Senior Developer Relations Manager - Data Processing and Data Science

NVIDIA · Santa Clara, CA

Manager

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 9aaec6da048b

Manager, Machine Learning Infrastructure - SIML

Apple · Seattle, WA

Manager Doctorate

2026-05-09

WA 2026-05-09

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, or a related field (or equivalent experience)
7+ years of software engineering experience, with 2+ years in a technical leadership or management role
Strong programming skills in one or more of: Python, Java, Go, C/C++ Solid understanding of machine learning fundamentals and ML system workflows
Proven experience in building and scaling distributed systems and backend infrastructure
Strong system design skills with expertise in at least one systems domain (e.g., data infrastructure, distributed systems, ML platforms)

Preferred

Experience building infrastructure for ML workflows (data pipelines, training systems, evaluation frameworks, or deployment systems)
Domain experience in areas such as AI/ML, computer vision, NLP, or related fields
Experience working with large-scale datasets and compute-intensive systems
Experience improving developer productivity through tooling and platform abstractions
Ability to operate effectively in cross-functional, fast-paced environments with evolving requirements

Responsibilities

Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies.
We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple's ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..). We are seeking an Engineering Manager to lead the development of scalable, high-performance infrastructure that powers product-focused machine learning initiatives.
In this role you will lead a team responsible for building and operating infrastructure that enables large-scale data processing (terabytes and beyond) across domains such as image generation, large language models (LLMs), computer vision, natural language processing, human-computer interaction, and text recognition. This includes designing systems for dataset creation and management, ingesting annotated and inferred data, and delivering seamless access to high-quality data for ML researchers and engineers.
A key part of this role is driving systems that enable deeper understanding of model behavior-such as failure mode analysis, evaluation pipelines, and benchmarking frameworks-to accelerate iteration velocity and improve model quality. You will work across the stack, tackling challenges ranging from low-level distributed systems and compute efficiency to building stable, intuitive interfaces for internal users.
As a leader, you will partner closely with cross-functional teams including ML researchers, product teams, and platform engineering to define roadmaps, align priorities, and deliver impactful solutions. You will play a critical role in shaping how ML systems are developed, evaluated, and scaled from early experimentation to production.

View full posting on CareerOneStop → ID: d0fb3fc55c81

Sr Systems Development Manager, ADC Analytics and Machine Learning

Amazon · Seattle, WA

Manager Bachelor's

2026-05-09

WA 2026-05-09

Requirements

Bachelor's degree in Computer Science or a related field
Proficiency in Linux based operating systems
Experience designing, building, and operating large-scale distributed systems or web services
Experience in managing large scale infrastructure and automation
Current, active US Government Security Clearance of TS/SCI with Polygraph

Preferred

Experience delivering large-scale infrastructure products that support Tier-1 mission critical services with a focus on privacy, security, availability, and efficiency
5+ years of managing an engineering team operating at scale experience
Expertise in Linux based operating systems
Experience developing and improving operational documentation, procedures and workflows
Current, active US Government Security Clearance of Top Secret with SCI eligibility or above

Responsibilities

Build a best-in-class engineering team that delivers excellent results
Design and develop state-of-the-art approaches to solving complex and ambiguous problems
Cultivate engineering and operational excellence through metrics and continuous learning
Mentor and grow others to take on increasingly higher responsibilities
Help raise the bar on technical excellence
Show thought leadership
Communicate proficiently and concisely to different audiences

View full posting on CareerOneStop → ID: 81ea4aacf8f1

Technical Project Manager - Machine Learning & Data Science

Cadmus · Olympia, WA

Manager Bachelor's

2026-05-09

WA 2026-05-09

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 61a801000082

Technical Project Manager - Machine Learning & Data Science

Cadmus · Boise, ID

Manager

2026-05-09

ID 2026-05-09

View full posting on CareerOneStop → ID: cf89a8291802

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salem, OR

Manager

2026-05-09

OR 2026-05-09

View full posting on CareerOneStop → ID: c698c99d5e8a

Technical Project Manager - Machine Learning & Data Science

Cadmus · Helena, MT

Manager

2026-05-09

MT 2026-05-09

View full posting on CareerOneStop → ID: fbc3bdcb768b

Technical Project Manager - Machine Learning & Data Science

Cadmus · Cheyenne, WY

Manager

2026-05-09

WY 2026-05-09

View full posting on CareerOneStop → ID: 9d7297b806a8

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salt Lake City, UT

Manager

2026-05-09

UT 2026-05-09

View full posting on CareerOneStop → ID: 0506b0505022

Technical Project Manager - Machine Learning & Data Science

Cadmus · Carson City, NV

Manager

2026-05-09

NV 2026-05-09

View full posting on CareerOneStop → ID: cc6d645b5e79

Technical Project Manager - Machine Learning & Data Science

Cadmus · Bismarck, ND

Manager

2026-05-09

ND 2026-05-09

View full posting on CareerOneStop → ID: 79d40124f546

Technical Project Manager - Machine Learning & Data Science

Cadmus · Pierre, SD

Manager

2026-05-09

SD 2026-05-09

View full posting on CareerOneStop → ID: 2e70b08f25f3

Manager, Machine Learning Infrastructure - SIML

Apple · Cupertino, CA

Manager

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 23a872893084

Senior Manager, Data Science - LLM Customization Team

Capital One · San Jose, CA

Manager

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 75b470169089

Technical Project Manager - Machine Learning & Data Science

Cadmus · Phoenix, AZ

Manager

2026-05-09

AZ 2026-05-09

View full posting on CareerOneStop → ID: b6ebd2f63311

Technical Project Manager - Machine Learning & Data Science

Cadmus · Santa Fe, NM

Manager

2026-05-09

NM 2026-05-09

View full posting on CareerOneStop → ID: a2cc8052a938

Technical Project Manager - Machine Learning & Data Science

Cadmus · Denver, CO

Manager

2026-05-09

CO 2026-05-09

View full posting on CareerOneStop → ID: 99b75ea021f4

Technical Project Manager - Machine Learning & Data Science

Cadmus · Lincoln, NE

Manager

2026-05-09

NE 2026-05-09

View full posting on CareerOneStop → ID: b9ee6c6930db

Technical Project Manager - Machine Learning & Data Science

Cadmus · Topeka, KS

Manager

2026-05-09

KS 2026-05-09

View full posting on CareerOneStop → ID: 11fedb997984

Technical Project Manager - Machine Learning & Data Science

Cadmus · Oklahoma City, OK

Manager

2026-05-09

OK 2026-05-09

View full posting on CareerOneStop → ID: 53e6e1816b1a

Senior Manager, Data Science - Credit Review

Capital One · Plano, TX

Manager

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: 08a9129e239d

Technical Project Manager - Machine Learning & Data Science

Cadmus · Saint Paul, MN

Manager

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: c17ea691a624

Technical Project Manager - Machine Learning & Data Science

Cadmus · Des Moines, IA

Manager

2026-05-09

IA 2026-05-09

View full posting on CareerOneStop → ID: 4c016d5f93c7

Technical Project Manager - Machine Learning & Data Science

Cadmus · Jefferson City, MO

Manager

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: b8e3d50af012

Technical Project Manager - Machine Learning & Data Science

Cadmus · Little Rock, AR

Manager

2026-05-09

AR 2026-05-09

View full posting on CareerOneStop → ID: 713517ce4320

Technical Project Manager - Machine Learning & Data Science

Cadmus · Baton Rouge, LA

Manager

2026-05-09

LA 2026-05-09

View full posting on CareerOneStop → ID: 71d45038859f

Technical Project Manager - Machine Learning & Data Science

Cadmus · Madison, WI

Manager

2026-05-09

WI 2026-05-09

View full posting on CareerOneStop → ID: d99cbbf4ddea

Manager, Data Scientist - US Card DFS Acquisitions

Capital One · Chicago, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: 626dd48ed2d3

Senior Manager, Data Science - Credit Review

Capital One · Riverwoods, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: a10d7323b705

Senior Manager, Data Science - Model Risk Office

Capital One · Chicago, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: 8859d0d6e11b

Technical Project Manager - Machine Learning & Data Science

Cadmus · Springfield, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: d61ecd1528a1

Technical Project Manager - Machine Learning & Data Science

Cadmus · Jackson, MS

Manager

2026-05-09

MS 2026-05-09

View full posting on CareerOneStop → ID: e967eaecf112

Technical Project Manager - Machine Learning & Data Science

Cadmus · Montgomery, AL

Manager

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: d17262f13c4f

senior manager, Data Science (Nashville, TN)

Starbucks · Nashville, TN

Manager

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: 14de9b7d79c0

Technical Project Manager - Machine Learning & Data Science

Cadmus · Nashville, TN

Manager

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: fd355074ffac

Technical Project Manager - Machine Learning & Data Science

Cadmus · Frankfort, KY

Manager

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: 2f8b5d238c39

Manager, Data Science, Outbound Communications

Amazon · Seattle, WA

Manager Master's

2026-05-08

WA 2026-05-08

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

You will lead applied scientists, data scientists and business intelligence engineers to:
Optimize Outbound's inbox management and planning system to personalize frequency, send-time and relevance bar of our messages to customers.
Design and execute large-scale experiments such as multi-arm elasticity tests or RCTs to measure and improve incrementality/performance of our models.
Drive development of HVA propensity models (opt-out, purchase, etc.) to drive intended behavior of customers to their next stage of shopping and engagement with Amazon.
Drive AI-based transformation in data accuracy and reporting: migrating and enhancing the self-serve analytics capabilities developed by the team, automating WBR preparation, building anomaly detection, etc.
Own financial planning frameworks for outbound performance including QxG/HVE forecasting and ROI measurement for paid channel investments.
In addition, you will:
Hire, develop, and mentor scientists and BIEs while partnering cross-functionally with engineering, product, marketing, and partner science teams (CBA, P13N, CFV) to productionize solutions at scale.
Create, align and evolve your team's roadmap by prioritizing across multiple competing priorities using high judgement decisions.

View full posting on CareerOneStop → ID: 1db4bc78fe2e

AI Engineer / Data Scientist, AI Sr. Manager

PwC · Chicago, IL

Manager

2026-05-08

IL 2026-05-08

View full posting on CareerOneStop → ID: d4c45f66dfb1

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Seattle, WA

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: 686e59cf50a7

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Olympia, WA

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: d43ded705913

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Portland, OR

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: 8925bf24e604

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Salem, OR

Manager

2026-05-07

OR 2026-05-07

View full posting on CareerOneStop → ID: 04d793fa540b

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Salt Lake City, UT

Manager

2026-05-07

UT 2026-05-07

View full posting on CareerOneStop → ID: 950eb3d6f74b

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Las Vegas, NV

Manager

2026-05-07

NV 2026-05-07

View full posting on CareerOneStop → ID: 62a66b78decd

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Carson City, NV

Manager

2026-05-07

NV 2026-05-07

View full posting on CareerOneStop → ID: 767fb86be729

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Tucson, AZ

Manager

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: b235b1a58dcf

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Phoenix, AZ

Manager

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: 2acad43ac117

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Topeka, KS

Manager

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: 4f615c95db8e

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Wichita, KS

Manager

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: dfc4dcb32d09

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Oklahoma City, OK

Manager

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: 69f41d7b91cc

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Tulsa, OK

Manager

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: c52ad09241a2

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Saint Paul, MN

Manager

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: c9108111713a

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Minneapolis, MN

Manager

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: f567fa15204c

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Des Moines, IA

Manager

2026-05-07

IA 2026-05-07

View full posting on CareerOneStop → ID: 00679a8c0d15

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Kansas City, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: a6ac77a76df9

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Saint Louis, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 3e73471ba07a

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Jefferson City, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 599a110bc887

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Rogers, AR

Manager

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: 1254779aeb62

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Little Rock, AR

Manager

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: eb2ba6e053cd

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · New Orleans, LA

Manager

2026-05-07

LA 2026-05-07

View full posting on CareerOneStop → ID: 461153f1a368

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Baton Rouge, LA

Manager

2026-05-07

LA 2026-05-07

View full posting on CareerOneStop → ID: 60c555056e6b

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Madison, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: bb8133a7f334

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Milwaukee, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: d569510d3bc5

R&D Senior Manager - Data Science

Amcor · Neenah, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: 71e85b95eff3

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 154c84de7067

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Springfield, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 294e866751c0

Business Operations Manager - Machine Learning and AI

JPMorgan Chase · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: dc75cfe2234f

Data Scientist / Portfolio Risk Manager

BMO Financial Group · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 1f61d7aa1149

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Birmingham, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: 183110f78e37

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Montgomery, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: f2b17a85cd65

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Huntsville, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: a0b76d6fbbe1

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Chattanooga, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 3a476aa91531

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Memphis, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 749d09bba52f

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Nashville, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 874834a87f72

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Frankfort, KY

Manager

2026-05-07

KY 2026-05-07

View full posting on CareerOneStop → ID: f25222f8438d

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Louisville, KY

Manager

2026-05-07

KY 2026-05-07

View full posting on CareerOneStop → ID: 6bc808580c4a

Senior Manager, Innovation Hub Technical Lead - Data Science

Pricewaterhousecoope · Denver, CO

Manager

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 41551fefe866

Manager, Data Scientist - Credit Review

Capital One · Riverwoods, IL

Manager

2026-05-05

IL 2026-05-05

View full posting on CareerOneStop → ID: 911ccd240fcd

Technical Program Manager, MADS - Measurement and Data Science

Amazon · Seattle, WA

Manager

2026-05-02

WA 2026-05-02

Requirements

5+ years of technical product or program management experience
3+ years of software development experience
5+ years of technical program management working directly with software engineering teams experience
Experience managing programs across cross functional teams, building processes and coordinating release schedules
Experience building and evaluating system-level technical design
Experience developing and executing/delivering product and technical roadmaps

Preferred

5+ years of project management disciplines including scope, schedule, budget, quality, along with risk and critical path management experience
Experience defining KPI's/SLA's used to drive multi-million dollar businesses and reporting to senior leadership

Responsibilities

Collaborate with team members to determine and prioritize features and software releases.
Implement mechanisms/tools to provide an accurate view of current feature usage, roadmap and help determine future deliveries.
Collaborate with partners to regularly deep dive on products and drive additional features where necessary.
Drive the implementation and management of Hackathon features so they can be merged into mainline.

View full posting on CareerOneStop → ID: 83af3c8aca76

Manager III, Data Science - AMZ9749732

AMAZON WEB SERVICES, INC. · Seattle, WA

Manager Master's

2026-05-02

WA 2026-05-02

[MULTIPLE POSITIONS AVAILABLE]{.underline} [Employer]{.underline}: AMAZON WEB SERVICES, INC. [Offered Position]{.underline}: Manager III, Data Science [Job Location]{.underline}: Seattle, Washington [Job Number]{.underline}:

View full posting on CareerOneStop → ID: c3e6703f8053

Actuary, Data Science, Global Risk Management &Claims

Amazon · Seattle, WA

Manager Bachelor's

2026-05-01

WA 2026-05-01

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

? Collaborate with risk management and claims team to identify insurance gaps, propose solutions, and measure impacts insurance brings to the business
? Develop models for new and existing insurance programs utilizing actuarial and data science techniques in innovative ways
? Build forecasts and analyses for businesses under rapid growth, including trend studies, loss distribution analysis, ILF development, and industry benchmarks
? Create processes to monitor loss cost and trends
? Propose and implement loss prevention initiatives with impact on insurance costs in mind
? Advise underwriting decisions with analysis on exposure risk profile
? Support insurance cost budgeting activities
? Collaborate with external vendors and other internal science teams to extract insurance insight
? Conduct other ad hoc analyses and risk modeling as needed

View full posting on CareerOneStop → ID: ea009793ed95

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Olympia, WA

Manager Doctorate

2026-05-01

WA 2026-05-01

Requirements

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases

Preferred

Ph.D. in Physics, Computer Science, Mathematics, or a related field with a strong focus on quantum information or quantum computing.
At least 7 years of experience in quantum computing research and development.
At least 7 years of experience partnering with quantum hardware developers to implement and evaluate algorithms.
At least 7 years of experience in quantum algorithms (e.g. Shor's algorithm, Grover's algorithm, Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA)).
At least 7 years of experience in quantum information theory and quantum computing applied to Machine Learning.
Excellent verbal and written communication skills with the ability to effectively communicate technical advances and strategy to research scientists, engineering teams, senior executives, and non-technical audiences.
Knowledge of advanced quantum hardware and their associated control systems.
Experience with large-scale classical simulation of quantum systems (e.g., with tensor networks or state-vector simulators).
Experience with production-level quantum hardware or cloud-based quantum services.
Worked with datasets or systems involving 100+ qubits.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is open to hiring a Remote Employee for this opportunity.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Remote (Regardless of Location): $209,000 - $238,500 for Sr Mgr, Data Science
McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.

View full posting on CareerOneStop → ID: 9ee44c336ec7

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Boise, ID

Manager

2026-05-01

ID 2026-05-01

View full posting on CareerOneStop → ID: c1fd030d604b

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Salem, OR

Manager

2026-05-01

OR 2026-05-01

View full posting on CareerOneStop → ID: af27b0f9b4a0

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Helena, MT

Manager

2026-05-01

MT 2026-05-01

View full posting on CareerOneStop → ID: 334224b827f1

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Cheyenne, WY

Manager

2026-05-01

WY 2026-05-01

View full posting on CareerOneStop → ID: 8b6a458d59f1

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Salt Lake City, UT

Manager

2026-05-01

UT 2026-05-01

View full posting on CareerOneStop → ID: 085cfa0a1545

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Carson City, NV

Manager

2026-05-01

NV 2026-05-01

View full posting on CareerOneStop → ID: 94e6bf3812f2

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Bismarck, ND

Manager

2026-05-01

ND 2026-05-01

View full posting on CareerOneStop → ID: 58ecc876c6a9

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Pierre, SD

Manager

2026-05-01

SD 2026-05-01

View full posting on CareerOneStop → ID: 3516d69ff7df

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Phoenix, AZ

Manager

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: a9a1756d8755

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Santa Fe, NM

Manager

2026-05-01

NM 2026-05-01

View full posting on CareerOneStop → ID: 1087cb8071fc

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Denver, CO

Manager

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: c84d7137cf0b

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Lincoln, NE

Manager

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: 95d300bbdfa3

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Topeka, KS

Manager

2026-05-01

KS 2026-05-01

View full posting on CareerOneStop → ID: 4dca2b2d54ba

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Oklahoma City, OK

Manager

2026-05-01

OK 2026-05-01

View full posting on CareerOneStop → ID: 5100e2884ed2

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Saint Paul, MN

Manager

2026-05-01

MN 2026-05-01

View full posting on CareerOneStop → ID: 5506c354d6df

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Des Moines, IA

Manager

2026-05-01

IA 2026-05-01

View full posting on CareerOneStop → ID: 8e46efefa018

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Jefferson City, MO

Manager

2026-05-01

MO 2026-05-01

View full posting on CareerOneStop → ID: 891c1423380c

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Little Rock, AR

Manager

2026-05-01

AR 2026-05-01

View full posting on CareerOneStop → ID: 56749da5a207

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Baton Rouge, LA

Manager

2026-05-01

LA 2026-05-01

View full posting on CareerOneStop → ID: 967f79861ff1

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Madison, WI

Manager

2026-05-01

WI 2026-05-01

View full posting on CareerOneStop → ID: ebcd06933b8f

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Jackson, MS

Manager

2026-05-01

MS 2026-05-01

View full posting on CareerOneStop → ID: 1676512544b3

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Montgomery, AL

Manager

2026-05-01

AL 2026-05-01

View full posting on CareerOneStop → ID: 8cf2121613a5

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Nashville, TN

Manager

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: 7f891cef27c3

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Frankfort, KY

Manager

2026-05-01

KY 2026-05-01

View full posting on CareerOneStop → ID: 8930a868be22

(USA) Senior Manager, Data Science, First Mile Strategy

Walmart · Bentonville, AR

Manager

2026-04-29

AR 2026-04-29

View full posting on CareerOneStop → ID: 21c675a4d729

(USA) Senior Manager, Data Science (AI Technical Lead) - Next-Gen Customer Engagement & Returns

Walmart · Bentonville, AR

Manager

2026-04-28

AR 2026-04-28

View full posting on CareerOneStop → ID: 45165b2af88f

(USA) Senior Manager, Data Science - eCommerce Strategy

Walmart · Bentonville, AR

Manager

2026-04-25

AR 2026-04-25

View full posting on CareerOneStop → ID: eac9aacbad2d

(USA) Senior Manager, Data Science

Walmart · Bellevue, WA

Manager Doctorate

2026-04-23

WA 2026-04-23

Requirements

Deep understanding of machine learning, statistical modeling, and data science techniques used for risk mitigation in e-commerce or marketplace environments.
Proven ability to build, deploy, and optimize complex data science models to identify and mitigate fraud, performance, and operational risks.
Proficiency in tools and languages such as Python, R, Spark, Scala , and machine learning frameworks (e.g., TensorFlow, PyTorch, XGBoost) to develop and deploy risk models.
Ability to understand the end-to-end risk management process, from data ingestion and feature engineering to model deployment and real-time decision making.
5-8 years of experience in leading teams or projects related to data science, including mentoring junior data scientists and guiding technical teams toward best practices in model development and deployment.
Comfortable navigating complex and uncertain situations, making data-driven decisions to improve risk management strategies in a fast-evolving environment.
Strong ability to translate complex data science concepts into clear, actionable insights for non-technical stakeholders across the organization.
Understanding how data science and risk management intersect with broader business objectives and the ability to align risk strategies with organizational goals.
Option 1 : Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, or related field, with 5-8 years of hands-on experience in data science, machine learning, or risk management.
Option 2 : Master's degree in a related field (e.g., Data Science, Machine Learning, Statistics, Applied Mathematics) with at least 3-5 years of applied experience working on data-driven risk management or fraud prevention.
Option 3 : 8-10 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting.
_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.

Preferred

Expertise in using advanced machine learning techniques such as deep learning, reinforcement learning, or anomaly detection for fraud detection or risk mitigation.
Experience with big data technologies like Apache Spark , Hadoop , and cloud-based data solutions (e.g., AWS, Google Cloud) to build scalable risk management platforms.
Proficiency in data manipulation and analysis tools such as Pandas, NumPy , and SQL for data wrangling, feature engineering, and analysis.
Strong background in model evaluation techniques including ROC/AUC, confusion matrices, precision/recall, and F1 scores, as well as experience with A/B testing and model validation
_Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.
Masters: Business Administration, Masters: Information Systems, Masters: Statistics
*Primary Location...
10900 Ne 4th St, Bellevue, WA 98004, United States of America
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

Responsibilities

The Senior Manager, DataScience will lead a team of data scientists to define, implement, test, and deploy decision strategies aimed at mitigating fraud and performance risks for Walmart Marketplace. In this role, you will work closely with cross-functional teams, including product, engineering, and data science, to continuously monitor, investigate, and respond to emerging risk trends. You'll be responsible for leveraging advanced data science methodologies to develop and refine risk management models, ensuring the strategies are effective and scalable across both domestic and international portfolios.
*How You'll Make an Impact:
Drive Data Science Innovation to protect the integrity of the Marketplace by applying advanced statistical methods, machine learning, and AI techniques to identify and mitigate fraud and performance risks.
Support Marketplace Growth by designing and implementing scalable, data-driven risk management solutions that align with key business objectives and growth targets.
Provide technical leadership and mentorship to your team, overseeing the development of decision models, managing model performance, and ensuring they are optimized for both accuracy and scalability.
Apply Advanced Data Science Techniques such as predictive modeling, supervised and unsupervised machine learning, deep learning, and anomaly detection to continuously improve risk strategies.
Collaborate Across Teams to integrate data science models with business processes, ensuring alignment between product, engineering, and data teams to address key risk areas effectively.
Monitor the performance of deployed models, identify opportunities for improvement, and iterate to enhance their predictive power and robustness in mitigating risks.
Develop Test & Measurement Frameworks to validate model effectiveness, utilizing rigorous A/B testing, statistical testing, and model evaluation to refine decision strategies.
Foster Innovation by exploring cutting-edge data science techniques, identifying opportunities to optimize decision-making, and driving improvements in risk management capabilities.

View full posting on CareerOneStop → ID: 4bb83fb26716

Engineering Manager, Machine Learning Operations

PitchBook Data · Seattle, WA

Manager

2026-04-23

WA 2026-04-23

Responsibilities

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.
We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!
As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook's MLOps team. The team is responsible for enabling PitchBook's Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team's work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.
Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
Ensure MLOps roadmap items are delivered on time and have exceptional quality
Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks(commercial and open source), that can be leveraged to improve PitchBook's AI capabilities
Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers

View full posting on CareerOneStop → ID: a3005c69a3e3

Principal Product Manager, Data Science & Market Research

Microsoft Corporation · Redmond, WA

Manager Bachelor's

2026-04-23

WA 2026-04-23

Requirements

Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience..
*Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

Preferred

8 years of experience in product management, data science, market research, or strategic analytics, preferably in a platform or developer-focused organization.
Solid quantitative skills with demonstrated ability to design research, analyze large datasets, and extract actionable insights.
Ability to translate data and research findings into product strategy and executive-ready recommendations.
Strong communication skills with the ability to present complex analysis clearly to technical and non-technical audiences.
Experience working cross-functionally with engineering, product, and business teams.
Experience with developer platforms, developer tools, or application frameworks.
Familiarity with telemetry systems, experimentation frameworks, or BI/analytics platforms (e.g., Power BI, Kusto, Azure Data Explorer).
Background in competitive intelligence, market sizing, or ecosystem analysis for technology platforms.
Understanding of the Windows developer ecosystem, including Win32, .NET, WinUI, and cross-platform frameworks.
Experience with data visualization and building executive dashboards that drive organizational alignment.
Product Management IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Define and own the data science and market research strategy for the Windows Platform & Developer organization, aligning research priorities to business and product goals.
Build and maintain analytical frameworks that track platform health, developer adoption, ecosystem growth, and competitive positioning across Windows, macOS, Linux, and web/cross-platform alternatives.
Deliver actionable market intelligence on developer trends, framework adoption and enterprise modernization patterns.
Partner with engineering, product, and leadership teams to define KPIs, instrument telemetry, and build dashboards that drive data-informed decision-making.
Lead primary and secondary research-developer surveys, competitive analysis, win/loss studies, and ecosystem assessments-to surface opportunities and risks.
Translate complex data into clear, compelling narratives for senior leadership to support investment decisions, roadmap prioritization, and executive reviews.
Engage with developer communities, enterprise customers, ISV partners, and internal stakeholders to validate hypotheses and ground insights in real-world signals.

View full posting on CareerOneStop → ID: ba3e52ea23e1

(USA) Senior Manager, Data Science

Walmart · Bentonville, AR

Manager

2026-04-18

AR 2026-04-18

View full posting on CareerOneStop → ID: 2fcc6e13bef6

Senior Manager, Data Science - Merchandising Analytics

Walmart · Bentonville, AR

Manager

2026-04-17

AR 2026-04-17

View full posting on CareerOneStop → ID: 6c63b139c5dd

(USA) Senior Manager, Data Science- Supply Chain Strategy

Walmart · Bentonville, AR

Manager

2026-04-15

AR 2026-04-15

View full posting on CareerOneStop → ID: 9e46935c6b8e

(USA) Senior Manager, Data Science - Supply Chain Strategy

Walmart · Bentonville, AR

Manager

2026-04-11

AR 2026-04-11

View full posting on CareerOneStop → ID: 46ea34a7bb22

Payer Healthcare Data Scientist, Manager

PwC · Las Vegas, NV

Manager

2026-04-04

NV 2026-04-04

View full posting on CareerOneStop → ID: b544b5355e36

Payer Healthcare Data Scientist, Manager

PwC · Oklahoma City, OK

Manager

2026-04-04

OK 2026-04-04

View full posting on CareerOneStop → ID: 8539fe57388c

Payer Healthcare Data Scientist, Manager

PwC · New Orleans, LA

Manager

2026-04-04

LA 2026-04-04

View full posting on CareerOneStop → ID: 43f34efe2062

Manager- Applied Sciences / Machine Learning

Microsoft Corporation · Redmond, WA

Manager Doctorate

2026-04-03

WA 2026-04-03

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
3+ years of people management experience.

Preferred

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
8+ years of industry experience in software engineering and/or machine learning, with prior experience leading teams or technical leadership roles.
Solid hands-on background in machine learning, including LLMs, NLP, or recommendation systems.
Proven track record of delivering large-scale, production-grade ML systems.
Experience leading or owning critical projects in recommendation systems or AIGC scenarios.
Proficiency in programming languages such as C/C++, C#, Java, and/or Python.
Demonstrated experience managing and growing ML teams, including performance management and career development.
Solid expertise in deep learning frameworks such as TensorFlow or PyTorch.
Experience with LLM fine-tuning, evaluation, and real-world product deployment.
Experience leading projects through full product lifecycle, from concept to launch and iteration.
Background in distributed systems and large-scale data processing.
Solid foundation in data structures, algorithms, and system design.
Experience with large-scale data analytics tools such as Spark.

Responsibilities

Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering.
Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation.
Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production.
Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact.
Champion innovation in AIGC applications, ranking, and recommendation algorithms.
Mentor and elevate the team, fostering a culture of technical excellence, collaboration, and continuous learning.
Communicate progress, insights, and strategy to senior leadership and stakeholders.

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