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Business Intelligence Analysts

15-2051.01 Bright Outlook $158K
7+20
postings · Doctorate
Career stage: All Intern (37) Entry-level (30) Mid-level (464) Senior (384) Manager (158) Director (57)
Education: All Associate's (5) Bachelor's (104) Master's (70) Doctorate (7)
What do these filters mean?
Career stage is read from the job title. Use it to find jobs aimed at where you are right now:
  • Intern You can apply while still in school.
  • Entry-level Designed for new graduates.
  • Mid-level Typically expects internship or 2-3 years of experience.
  • Senior Established career role — usually 5+ years experience.
  • Manager Leads a team of engineers, not an early-career role.
  • Director Executive role — typically 10+ years of career experience.
Education is the highest degree the posting explicitly mentions. Postings that don't say are not filtered out — they appear under "All".
Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director
Merck · Olympia, WA
Director Doctorate
2026-05-20
Requirements
  • Active Listening, Actuarial Science, Big Data, Business Acumen, Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Detail-Oriented, Health Data Analytics, Medical Insurance Coding, Object-Oriented Design (OOD), Object Oriented Modeling, Object-Oriented Programming (OOP), Software Development, Stakeholder Relationship Management, Trend Knowledge, Version Control
Preferred
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 10 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience
  • Experience in Global Medical Affairs
  • Experience using CMS quality data
  • Exposure to payer analytics or Market Access analytics
  • Advanced skills in Microsoft Excel, PowerPoint, and Word
  • Experience with visualization software such as Tableau, Spotfire, Qlik, or related
  • Exposure to Big Data technology such as AWS Redshift
  • Experience using version control and object-oriented programming
  • Experience with medical coding
Responsibilities
  • The Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director assists the V&I organization in discovering information hidden in data to make data driven strategic decisions for the organization.
  • This role requires a unique combination of skills to gain the trust of therapeutic area and regional colleagues, have an innovative mindset to think through novel ways to help us make better decisions, and execute on the idea by gathering the necessary data and developing analytic solutions that will fulfill our internal stakeholders' needs. This is a great opportunity for a self-motivated individual with strong business acumen along with technical competence.
  • Relevant Enterprise Leadership Skills (ELS) for this role include: Execution Excellence, Ownership and Accountability, and Business Savviness.
  • Partners with internal stakeholders to understand the needs of V&I.
  • Identifies appropriate data sources to address the needs of V&I.
  • Ensures high quality, rigorous and readily interpretable deliverables.
  • Develops data visualizations and presentation decks to communicate findings.
  • Provides recommended actions with stakeholders from senior and executive leadership teams.
  • Contributes toward a collaborative environment where the Medical Data Analytics Center team 1) maintains an entrepreneurial spirit 2) has a strong understanding of healthcare data and technology 3) can identify and use new data sources.
  • Keeps abreast of the latest trends in the field through continuous learning and proactively championing new methods to help solve critical and emerging V&I problems and drive V&I activities.
  • Collaborates and partners with peers in other functions (Human Health (HH), Outcomes Research, etc.) on cross-functional analytics projects and to drive efficiencies in developing innovative quantitative analyses.
  • Manages external vendors.
  • Develops and owns scalable-analytic products that fulfill stakeholders needs.
  • Develops and maintains internal databases, data pipelines, and supporting documentation.
  • Designs and develops analyses to draw inferences and conclusions to inform decision-making for V&I.
  • Provides recommended actions to stakeholders.
  • *Required Qualifications , Skills, & Experience
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 1 year of relevant job experience.
  • Demonstrated experience in Advanced Analytics, Statistical Modeling, NLP, AI, Machine Learning
  • Expertise in Python, object-oriented programming, and version control (e.g., git)
  • Experience with cloud computing services (e.g., AWS)
  • Experience using SQL and SQL relational databases
  • Experience analyzing real-world data assets including EMR and EHR
  • Strong analytical and problem-solving skills
  • Strong business acumen in the pharmaceutical industry
  • Ability to succinctly translate complex ideas and analytical results into actionable insights and recommended actions
  • Strong presentation skills
  • Experience in building effective cross-functional partnerships and working across global teams
  • Ability to influence peers and leaders
  • Strong listening skills
  • Attention to detail
  • An entrepreneurial spirit with a high degree of initiative, innovative thinking, and intellectual curiosity
  • High degree of personal integrity
View full posting on CareerOneStop → ID: 583b38901be0
Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director
Merck · Boise, ID
Director Doctorate
2026-05-20
Requirements
  • Active Listening, Actuarial Science, Big Data, Business Acumen, Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Detail-Oriented, Health Data Analytics, Medical Insurance Coding, Object-Oriented Design (OOD), Object Oriented Modeling, Object-Oriented Programming (OOP), Software Development, Stakeholder Relationship Management, Trend Knowledge, Version Control
Preferred
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 10 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience
  • Experience in Global Medical Affairs
  • Experience using CMS quality data
  • Exposure to payer analytics or Market Access analytics
  • Advanced skills in Microsoft Excel, PowerPoint, and Word
  • Experience with visualization software such as Tableau, Spotfire, Qlik, or related
  • Exposure to Big Data technology such as AWS Redshift
  • Experience using version control and object-oriented programming
  • Experience with medical coding
Responsibilities
  • The Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director assists the V&I organization in discovering information hidden in data to make data driven strategic decisions for the organization.
  • This role requires a unique combination of skills to gain the trust of therapeutic area and regional colleagues, have an innovative mindset to think through novel ways to help us make better decisions, and execute on the idea by gathering the necessary data and developing analytic solutions that will fulfill our internal stakeholders' needs. This is a great opportunity for a self-motivated individual with strong business acumen along with technical competence.
  • Relevant Enterprise Leadership Skills (ELS) for this role include: Execution Excellence, Ownership and Accountability, and Business Savviness.
  • Partners with internal stakeholders to understand the needs of V&I.
  • Identifies appropriate data sources to address the needs of V&I.
  • Ensures high quality, rigorous and readily interpretable deliverables.
  • Develops data visualizations and presentation decks to communicate findings.
  • Provides recommended actions with stakeholders from senior and executive leadership teams.
  • Contributes toward a collaborative environment where the Medical Data Analytics Center team 1) maintains an entrepreneurial spirit 2) has a strong understanding of healthcare data and technology 3) can identify and use new data sources.
  • Keeps abreast of the latest trends in the field through continuous learning and proactively championing new methods to help solve critical and emerging V&I problems and drive V&I activities.
  • Collaborates and partners with peers in other functions (Human Health (HH), Outcomes Research, etc.) on cross-functional analytics projects and to drive efficiencies in developing innovative quantitative analyses.
  • Manages external vendors.
  • Develops and owns scalable-analytic products that fulfill stakeholders needs.
  • Develops and maintains internal databases, data pipelines, and supporting documentation.
  • Designs and develops analyses to draw inferences and conclusions to inform decision-making for V&I.
  • Provides recommended actions to stakeholders.
  • *Required Qualifications , Skills, & Experience
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 1 year of relevant job experience.
  • Demonstrated experience in Advanced Analytics, Statistical Modeling, NLP, AI, Machine Learning
  • Expertise in Python, object-oriented programming, and version control (e.g., git)
  • Experience with cloud computing services (e.g., AWS)
  • Experience using SQL and SQL relational databases
  • Experience analyzing real-world data assets including EMR and EHR
  • Strong analytical and problem-solving skills
  • Strong business acumen in the pharmaceutical industry
  • Ability to succinctly translate complex ideas and analytical results into actionable insights and recommended actions
  • Strong presentation skills
  • Experience in building effective cross-functional partnerships and working across global teams
  • Ability to influence peers and leaders
  • Strong listening skills
  • Attention to detail
  • An entrepreneurial spirit with a high degree of initiative, innovative thinking, and intellectual curiosity
  • High degree of personal integrity
View full posting on CareerOneStop → ID: eab81ea94e0a
Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director
Merck · Salem, OR
Director Doctorate
2026-05-20
Requirements
  • Active Listening, Actuarial Science, Big Data, Business Acumen, Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Detail-Oriented, Health Data Analytics, Medical Insurance Coding, Object-Oriented Design (OOD), Object Oriented Modeling, Object-Oriented Programming (OOP), Software Development, Stakeholder Relationship Management, Trend Knowledge, Version Control
Preferred
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 10 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience
  • Experience in Global Medical Affairs
  • Experience using CMS quality data
  • Exposure to payer analytics or Market Access analytics
  • Advanced skills in Microsoft Excel, PowerPoint, and Word
  • Experience with visualization software such as Tableau, Spotfire, Qlik, or related
  • Exposure to Big Data technology such as AWS Redshift
  • Experience using version control and object-oriented programming
  • Experience with medical coding
Responsibilities
  • The Value & Implementation (V&I) Medical Data Analytics Center Data Enablement Associate Director assists the V&I organization in discovering information hidden in data to make data driven strategic decisions for the organization.
  • This role requires a unique combination of skills to gain the trust of therapeutic area and regional colleagues, have an innovative mindset to think through novel ways to help us make better decisions, and execute on the idea by gathering the necessary data and developing analytic solutions that will fulfill our internal stakeholders' needs. This is a great opportunity for a self-motivated individual with strong business acumen along with technical competence.
  • Relevant Enterprise Leadership Skills (ELS) for this role include: Execution Excellence, Ownership and Accountability, and Business Savviness.
  • Partners with internal stakeholders to understand the needs of V&I.
  • Identifies appropriate data sources to address the needs of V&I.
  • Ensures high quality, rigorous and readily interpretable deliverables.
  • Develops data visualizations and presentation decks to communicate findings.
  • Provides recommended actions with stakeholders from senior and executive leadership teams.
  • Contributes toward a collaborative environment where the Medical Data Analytics Center team 1) maintains an entrepreneurial spirit 2) has a strong understanding of healthcare data and technology 3) can identify and use new data sources.
  • Keeps abreast of the latest trends in the field through continuous learning and proactively championing new methods to help solve critical and emerging V&I problems and drive V&I activities.
  • Collaborates and partners with peers in other functions (Human Health (HH), Outcomes Research, etc.) on cross-functional analytics projects and to drive efficiencies in developing innovative quantitative analyses.
  • Manages external vendors.
  • Develops and owns scalable-analytic products that fulfill stakeholders needs.
  • Develops and maintains internal databases, data pipelines, and supporting documentation.
  • Designs and develops analyses to draw inferences and conclusions to inform decision-making for V&I.
  • Provides recommended actions to stakeholders.
  • *Required Qualifications , Skills, & Experience
  • Bachelor's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 8 years of relevant job experience; Master's degree (computer science, physics, mathematics, actuarial science, or equivalent) with 5 years of relevant job experience; PhD (computer science, physics, mathematics, actuarial science, or equivalent) with 1 year of relevant job experience.
  • Demonstrated experience in Advanced Analytics, Statistical Modeling, NLP, AI, Machine Learning
  • Expertise in Python, object-oriented programming, and version control (e.g., git)
  • Experience with cloud computing services (e.g., AWS)
  • Experience using SQL and SQL relational databases
  • Experience analyzing real-world data assets including EMR and EHR
  • Strong analytical and problem-solving skills
  • Strong business acumen in the pharmaceutical industry
  • Ability to succinctly translate complex ideas and analytical results into actionable insights and recommended actions
  • Strong presentation skills
  • Experience in building effective cross-functional partnerships and working across global teams
  • Ability to influence peers and leaders
  • Strong listening skills
  • Attention to detail
  • An entrepreneurial spirit with a high degree of initiative, innovative thinking, and intellectual curiosity
  • High degree of personal integrity
View full posting on CareerOneStop → ID: b8de2a34bde1
Business Intelligence Engineer, ADSP Product Operations & Analytics
Amazon · Seattle, WA
Mid-level Doctorate
2026-05-16
Requirements
  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • 3+ years of developing automated reporting experience
  • 2+ years of processing large, multi-dimensional datasets from multiple sources experience
  • 1+ years of performing statistical analysis experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience in Statistical Analysis packages such as R, SAS and Matlab
  • Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
Preferred
  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
Responsibilities
  • Investigate complex business challenges by identifying root causes of delivery gaps and operational inefficiencies while uncovering opportunities to optimize outcomes and improve overall health of business operations
  • Design and build resilient business intelligence solutions using Redshift, Oracle, and NoSQL databases that maintain accuracy despite data quality variations across multiple platforms and systems
  • Develop sophisticated data models and ETL pipelines that process large-scale datasets to support rapid business growth and evolving organizational needs
  • Create optimized SQL queries and data transformation workflows that convert raw data into actionable dashboards tracking key performance indicators, budget metrics, and operational efficiency
  • Partner with operations teams, stakeholders, and product managers to gather requirements and present performance insights that improve business outcomes
  • Innovate new metrics and measurement frameworks that capture effectiveness of emerging initiatives and capabilities
  • Communicate complex analyses on business trends and operational dynamics to stakeholders through clear documentation and presentations
  • Collaborate across engineering, data science, and business teams to build centralized data tools
View full posting on CareerOneStop → ID: fa11d9a0d448
Director of the Data Analytics Program & Instructor
Oregon State University · Corvallis, OR
Director Doctorate
2026-05-15
Requirements
  • Doctoral degree in statistics, biostatistics, or a related discipline.
  • Prior teaching experiences in Statistics or closely related field.
  • Strong oral and written communication skills including ability to communicate to diverse and disparate audiences.
  • Demonstrated commitment to promoting and enhancing inclusive excellence through inclusive teaching practices, curriculum design, and equitable learning environments.
  • This position is designated as a critical or security-sensitive position; therefore, the incumbent must successfully complete a criminal history check and be determined to be position qualified as per University Standard: 05-010 et seq. Incumbents are required to self-report convictions and those in youth programs may have additional criminal history checks every 24 months.
  • What We Would Like You to Have
  • Experience developing online, asynchronous courses.
  • Experience in mentoring students/or junior member in academic or professional settings.
  • Experience in working with real-world data problems, including applied or industry-relevant projects.
  • Demonstrated potential to establish and sustain partnership with industry and external stakeholders.
Responsibilities
  • Position Information
  • Department Statistics (Science) (SST)
  • Position Title Coordinator-Academic Program
  • Job Title Director of the Data Analytics Program & Instructo
  • Appointment Type Professional Faculty
  • The Department of Statistics at Oregon State University invites applications for a Director of the Data Analytics Program & Instructor. The incumbent will hold two appointments, a 0.30 FTE , 9-month professional faculty position as Director of the Data Analytics Program, and a 0.20 FTE , 9-month, Instructor position; reflecting duties in both academic and administrative areas.
  • Appointment at the Instructor rank is anticipated; however, appointment at a promoted rank may be considered depending upon the qualifications of the successful candidate.
  • This is a half time, 9-month Director of Data analytics (DA) program position in the Department of Statistics. This position teaches undergraduate and graduate statistics and data science courses. This position provides academic and administrative leadership for the DA graduate program. The Director oversees curriculum development and delivery, ensures academic quality and relevance, supports student success, and coordinates program operations in collaboration with faculty, staff, and administration. The role includes guiding strategic growth of the program, fostering connections with industry and external partners, and promoting experiential and data-driven learning opportunities. The Director typically teaches in the program and serves as the primary advocate for the MS in Data Analytics within and beyond the institution.
  • The position is expected to maintain a high standard of collegiality, professional integrity, and willingness to accept and cooperate in assignments. All faculty are also expected to be collegial and active members of their units and to perform appropriate service that contributes to the effectiveness of their departments, colleges, the university, and of their professions.
  • The mission of the Department of Statistics is to contribute to the overall objectives of Oregon State University and the Colleges of Science and Agriculture through excellence in research and education in the statistical sciences and through service to the university community, statistical profession, and society at large.
  • The College of Science provides a core instructional role at OSU , supporting the ideals of learning, discovery, and engagement that are the foundation of a land-grant university. The College embraces instruction and research, in disciplines ranging from the physical to the biological sciences that are based in unbiased inquiry and a dedication to discovery and innovation. The College of Science is committed to partnering with industry and public agencies to address some of the most compelling challenges of today and tomorrow.
  • OSU has an institution-wide commitment to diversity, multiculturalism, and community. We actively engage in recruiting and retaining a diverse workforce and student body that includes members of historically underrepresented groups. We strive to build and sustain a welcoming and supportive campus environment. OSU provides leadership opportunities for people interested in promoting and enhancing diversity, nurturing creativity and building community. All employees are responsible for helping to maintain and enhance OSU's collaborative and inclusive community that strives for equity and equal opportunity.
  • Working for Oregon State University is so much more than a job!
  • Oregon State University is a dynamic community of dreamers, doers, problem-solvers and change-makers. We don't wait for challenges to present themselves - we seek them out and take them on. We welcome students, faculty and staff from every background and perspective into a community where everyone feels seen and heard. We have deep-rooted mindfulness for the natural world and all who depend on it, and together, we apply knowledge, tools and skills to build a better future for all.
  • Top 1.4% university in the world
  • More research funding than all public universities in Oregon combined
  • 1 of 3 land, sea, space and sun grant universities in the U.S.
  • 2 campuses, 11 colleges, 12 experiment stations, and Extension programs in all 36 counties
  • 7cultural resource centers (https://hr.oregonstate.edu/work-life/diversity-and-cultural-resources) that offer education, celebration and belonging for everyone
  • 100+ undergraduate degree programs, 80+ graduate degrees plus hundreds of minor options and certificates
  • 35k+ students including more than 2.3k international students and 10k students of colo
  • 217k+ alumni worldwide
  • For more interesting facts about OSU visit:https://oregonstate.edu/about
  • Oregon State has a statewide presence with campuses in Corvallis and Bend, the OSU Portland Center and the Hatfield Marine Science Center on the Pacific Coast in Newport.
  • Oregon State's beautiful, historic and state-of-the-art main campus is located in one of America's best college towns. Corvallis is located close to the Pacific Ocean, the Cascade mountains and Oregon wine country. Nestled in the heart of the Willamette Valley, this beautiful city offers miles of mountain biking and hiking trails, a river perfect for boating or kayaking and an eclectic downtown featuring local cuisine, popular events and performances.
  • 60%Data Analytics (DA) Graduate Program Leadership
  • https://jobs.oregonstate.edu/position\_descriptions/179999
  • https://jobs.oregonstate.edu/position\_descriptions/179994
  • Posting Detail Information
  • Posting Number P09914UF
  • Number of Vacancies 1
  • Anticipated Appointment Begin Date 09/16/2026
  • Anticipated Appointment End Date
  • Posting Date 05/13/2026
  • Full Consideration Date 07/15/2026
  • Closing Date 07/30/2026
  • Indicate how you intend to recruit for this search Competitive / External - open to ALL qualified applicants
  • Special Instructions to Applicants
  • To ensure full consideration, applications must be received by July 15, 2026.Applications will continue to be accepted after the full consideration date, until a sufficient applicant pool has been achieved or the position is filled. The closing date is subject to change without notice to applicants.
  • When applying you will be required to attach the following electronic documents:
  • A cover letter indicating how your qualifications and experience have prepared you for this position; and
  • Personal Statement, uploaded as Other Document 1 (not to exceed one page), in which you:
  • Reflect on any aspect of your identity, values and experiences that contributed to your professional path up to this point; and
  • How you will contribute to promoting inclusive advising practices at our institution.
  • Letters of Reference will be requested on finalists only. When applying, you will be asked to provide the email address and telephone number for 3 referees who will be sent a secure quicklink that will allow them to upload the requested letters of reference on your behalf.
  • For additional information please contact:
  • xuel@oregonstate.edu
View full posting on CareerOneStop → ID: fd37ef27a6d1
Senior Data Analysis Manager, GTM Analytics - Capital One Software (Remote)
Capital One · Olympia, WA
Manager Doctorate
2026-05-10
Requirements
  • Currently has, or is in the process of obtaining a Bachelor's Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 7 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master's Degree plus at least 5 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.
  • At least 5 years of experience performing professional data analysis work
  • At least 5 years of experience leading and developing with open source data technologies
  • At least 2 years of experience managing people
Preferred
  • Master's Degree or PhD in a Finance, Economics, Statistics, Mathematics, Industrial Engineering, Operations Research, or a related field
  • At least 7 years of experience in statistical or econometrics hands-on work
  • At least 5 years of experience manipulating and performing analysis with large data sets
  • At least 5 years of experience in financial services industry
  • At least 5 years of experience in developing statistical or econometric models
  • At least 5 years of experience in validating statistical or econometric models
  • At least 2 years of experience with data governance
  • At least 2 years of experience with predictive analytics
  • At least 2 years of experience with B2B SaaS products
  • _At this time, Capital One will not sponsor a new applicant for employment authorization for this position._
  • 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): $182,500 - $208,300 for Sr. Data Analysis Manage
  • Richmond, VA: $182,500 - $208,300 for Sr. Data Analysis Manage
  • 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.
Responsibilities
  • Partnership : Partner with stakeholders across the GTM organization, including Sales, Sales Operations, Solutions Architecture, and Customer Success Leaders to identify and address reporting and analysis needs
  • Execution : Manage and sequence delivery of reporting and data needs, build business requirements and execute against these requirements. Own and drive multiple projects concurrently
  • Dashboarding and Visualization : Ability to create dashboards and data visualizations that deliver business insights and information at scale
  • Strategic & Analytic Orientation : A proven track record of decision making and problem solving based on analytics. Conceptual thinking skills must be complemented by a strong quantitative orientation and data driven approach
  • Collaboration : Ability to collaborate and work with business partners across the enterprise. You should foster innovation, drive critical decisions, hold business partners accountable, and be able to consistently deliver results in a fast growing, matrixed environment
  • Strong Executive Communication Skills : Impeccable written and oral communication credentials, coupled with the ability to deliver core business reports to GTM leadership
  • Clear Results Orientation : Display an intense focus on achieving both short and long term goals. You should be able to drive and execute an agenda in an uncertain and fluid environment, including the preparation of ad-hoc analysis and reports
  • People Leadership: Provide effective coaching, and consistent feedback. Establish clear expectations and actively develop your associates' skills.
View full posting on CareerOneStop → ID: a63151c12872
Senior Software Engineer, Google.org, Data Analytics
Google · Seattle, WA
Senior Doctorate
2026-04-29
Requirements
  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • Experience in SQL.
Preferred
  • Master's degree or PhD in Computer Science, or a related technical field.
  • 5 years of experience with data structures and algorithms.
  • 5 years of experience with performance and large-scale systems data analysis, visualization tools, or debugging.
  • Experience supporting non-profits or other philanthropic organizations.
Responsibilities
  • Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
  • We strive to organize the world's information to make it universally accessible and useful, but we know that relevance means something different to each person. The Social team recognizes that great information is more than pages -- it's also about relationships. We want all of Google's products to reflect something personal, and we're dedicated to making your Google experience centered around you.
  • The US base salary range for this full-time position is $174,000-$252,000 + 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/) .
  • Own the design and architecture of project components, scoping problems and recommending solutions for both short and long-term needs.
  • Drive the evaluation and recommendation of AI strategies (e.g., prompt engineering) to solve technical problems and increase team velocity.
  • Implement high-complexity technical solutions.
  • Design and execute testing strategies, including integration and performance testing, to ensure quality and reliability.
  • Guide implementation, ensuring the systems are scalable and maintainable.
  • 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: ea94affa2189

Related Postings (SOC 15-20 family)

AI and Data Science Engineer III Deloitte · Seattle, WA Mid-level Doctorate 2026-06-05
Requirements
  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years of experience in data science, analytics, or a related field - with direct experience in client-facing or consulting environments.
  • 4+ years of demonstrated proficiency in SQL for data extraction, transformation, and analysis across relational databases.
  • 4+ years of demonstrated proficiency in Python or R for statistical modeling and data wrangling.
  • 4+ years of hands-on experience with data visualization tools such as Tableau, Power BI, or equivalent platforms.
  • 4+ years of building analytics solutions end-to-end: from data ingestion and modeling to visualization and stakeholder presentation.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available
Preferred
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  • Proficiency in Python or R for statistical modeling and data wrangling.
  • Strong communication skills with the ability to convey complex analytical insights to diverse audiences.
  • 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 $122,000 to $240,500.
  • 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.
Responsibilities
  • Lead the design, development, and delivery of analytics solutions that address complex workforce and human capital challenges for clients across industries.
  • Build and maintain scalable data pipelines, dashboards, and reporting frameworks using SQL and Tableau (or equivalent visualization platforms).
  • Translate ambiguous business problems into structured analytical approaches, communicating findings and recommendations clearly to both technical and non-technical stakeholders.
  • Collaborate across service lines to embed AI-enabled capabilities and emerging data methodologies into client solutions.
  • Support business development efforts including proposals, client presentations, and thought leadership content.
  • Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.
  • Apply economic and statistical reasoning to interpret workforce trends, model scenarios, and support evidence-based decision-making.
  • A successful candidate would possess these skills:
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.
View posting →
Data Scientist Engineer - SFL Scientific Deloitte · Seattle, WA Mid-level Doctorate 2026-06-05
Requirements
  • Master's or Ph.D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, etc.)
  • 2+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
  • 2+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
  • 2+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Triton, RAPIDs, Kubeflow, and MLflow
  • 2+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
  • 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
  • 2+ years of experience working in a client-facing, consulting environment
  • 1+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
  • 1+ year of experience with LLM/GenAI use cases and developing RAG solutions, agent-based tools and services, and GenAI frameworks (i.e., LangChain, LangGraph, MCP, etc.)
  • 1+ year of experience with AWS Sagemaker or AWS ML Studio
  • 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 $95,600 to $188,400.
  • 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 posting →
Data Scientist, Finance Meta · Bellevue, WA Mid-level Doctorate 2026-06-05
Requirements
  • Bachelor's degree in a directly related field, or equivalent practical experience
  • A minimum of 12 years of work experience in analytics (minimum of 8 years with a Ph.D.)
  • Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
Preferred
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Master's or Ph.D. degree in a quantitative field
  • Experience working in a data science role at a hyperscaler / public cloud and / or a large customer of a public cloud company
  • Experience partnering cross-functionally with a wide range of teams, dealing with ambiguous and presenting technical content in an easy to understand manner to technical and non-technical teams
  • Knowledge of business outcomes and technology investments and experience connecting them to practical models for decision making
Responsibilities
  • Meta is seeking a Data Scientist to join the data science team in the Finance organization that partners very closely with Product, AI, Infrastructure, Finance and other Data Science teams across the company. These teams are building some of the most cutting edge and transformative AI products in the world that are being rolled out to Meta's 3 Billion+ users. Building these products and features requires tens of billions of dollars of capital each year over a sustained period of time. Managing and optimizing the deployment of this vast capital and the allocation of these resources requires a team that has technical expertise in AI and Infrastructure along with a solid understanding of data science, finance and operations. This position will use data and analysis to identify and solve product development's biggest challenges and will require an understanding of how AI and Infrastructure are built, operated and used to serve users. This role will help establish the ROI and company-wide prioritization of such investments and work on solving some of the most important technological problems of our times and also ensure that the company makes efficient investments. As an individual contributor, you will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a high-performing analytics community dedicated to skill development and career growth in analytics and beyond.
  • Work with large and complex data sets to solve a wide array of problems using different analytical and statistical approaches
  • Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to build and maintain end-to-end models for long range planning and strategic decisions
  • Build models to compute and explain Infrastructure OPEX and CAPEX costs at the company, product and resource levels
  • Leverage understanding of AI and Infrastructure to develop point-of-view on ROI of investments in Infrastructure and allocation of Infrastructure resources to various products and software platforms
  • Identify and measure success infrastructure investments through goal setting, forecasting, and monitoring of key metrics to understand trends
  • Help define resource allocation policies that are reasonable and actionable from a technical, operational and financial perspective
  • Work with product, engineering and data science teams to do technical, operational and business impact assessments of re-allocation of resources based on changing business needs, competitive landscape and product roadmaps
  • Maintain lineage of decisions around Infrastructure investments and assumptions under which those decisions were made to drive accountability for outcomes across the company
  • Define, understand, and test opportunities and levers to improve the our models, and drive roadmaps through your insights and recommendations
  • Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
View posting →
Distinguished, Data Scientist Walmart · Bellevue, WA Senior Doctorate 2026-06-05
Requirements
  • Bachelor's with >20years, Masters > 17yearsOR Ph.D. in Comp Science/Statistics/Mathematics with > 14years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics ora related area.
  • Experience of acting as a tech lead for > 10 years
  • _Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
  • Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 3: 8 years' experience in an analytics or related field.
Preferred
  • _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, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, 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.
  • *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
  • As a Distinguished Data Scientist in the Marketplace data sciences team, you'll have the opportunity to -
  • Drive innovative strategic solutionsfor Marketplaceutilizingadvanced SOTA AI and ML solutions at large scale and atacceleratedpace.
  • Drive data-derived insights by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
  • Work closely with Directors, Sr. Managers of Data Science, and leaders ofArchitecture,Engineering,Product& businessteams to drive the Organizational strategy aroundMarketplace.
  • Direct the gathering of data, assess datavalidityand synthesize data into large analytics datasets to support project goals
  • Mentor and guide a setof Data Scientists, Data Analystsacross IDC and UStodrive Marketplace growth and operation efficiencyusing advanced Machine Learning and Gen AI.
  • Utilize big data analytics and advanced data science techniques toidentifytrends, patterns, and discrepancies in data.Determineadditionaldata needed to support insights
  • Build and train AI/ML models for replication for future projects
  • Deploy andmaintainthe data science solutions
  • Communicate recommendations to business partners and influencefuture plansbased on insights
  • *Position Responsibility
  • Consult with product/business stakeholders on algorithmic recommendations and translate insights into actions.
  • Lead and mentor domain data science teams to deliver ML products on time.
  • Collaborate cross-functionally to drive end-to-end content improvement.
  • Research and develop innovative content-improvementsolutions leveragingmultilingual and multimodal foundation models.
  • Identifycomplex business opportunities solvable with advanced ML/Computer Vision; evaluate and prioritize business cases.
  • Define success criteria, deliverables, and KPIs; quantify and track business impact of ML products.
  • Establish model evaluation/testing standards and documentation; guide deployment viaMLOpsbest practices.
  • Communicate recommendations, influence partners globally, and drive innovation while upholding company values and ethics.
View posting →
AIML - ML Engineer, Responsible AI Apple · Seattle, WA Mid-level Doctorate 2026-06-04
Requirements
  • Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
  • Background in generative models, natural language processing, LLMs, or diffusion models
  • Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features
  • Experience working with crowd-based annotations and human evaluations
  • Experience working on explainability and interpretation of AI/ML models
  • Work with highly-sensitive content with exposure to offensive and controversial content
Preferred
  • BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
  • Proven track record of contributing to diverse teams in a collaborative environment
Responsibilities
  • Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
  • In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
  • Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle
  • Develop methods, models, and tools to interpret and explain failures in language and diffusion models
  • Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products
  • Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs
View posting →
Data Scientist - Pricing Microsoft Corporation · Redmond, WA Mid-level Doctorate 2026-06-04
Requirements
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
Preferred
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • Experience in Python, R, or similar languages
  • Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms.
  • Experience working with large-scale data and distributed systems.
  • Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
  • Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 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 $133,800.00 - $219,200.00 per year.
  • Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
Responsibilities
  • Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
  • Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
  • Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
  • Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
  • Data Visualization : Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights.
  • Thought Leadership : Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
  • Other : Embody our Culture (https://www.microsoft.com/en-us/about/corporate-values) and Values (https://careers.microsoft.com/us/en/culture)
View posting →
Machine Learning Engineer - News, Books, and Stocks Team Apple · Seattle, WA Mid-level Doctorate 2026-06-04
Requirements
  • MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
  • At least 2 years of experience shipping machine learning models in products.
  • Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
  • Ability to communicate effectively and collaborate with partner teams.
  • Commitment to encouraging an open and inclusive work environment.
Preferred
  • Ph.D. in Machine Learning, Computer Science, or related field.
  • At least 5 years of experience shipping machine learning models in products.
  • Experience with recommender systems.
  • Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
  • Experience delivering high quality software at scale.
  • Experience designing user-facing machine learning features with interdisciplinary partners.
Responsibilities
  • In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers. Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps!
  • Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day!
View posting →
Staff AI/ML Engineer - Future Sensing, Embodied AI General Motors · Olympia, WA Senior Doctorate 2026-06-04
Preferred
  • Experience in robotics or autonomous driving systems
  • Experience with architecting perception or sensory systems for automotive, robotics, or safety-critical platforms
  • Experience with system integration across sensors, calibration, compute, and onboard software pipelines
  • Experience with simulation, synthetic data, and sim-to-road evaluation workflows
  • Technical leadership experience including mentoring engineers and shaping major workstreams from concept to execution.
  • *Remote/Hybrid: This role is categorized as fully remote or hybrid.
  • *Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
  • The salary range for this role is $189,300.00 to $320,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
  • *Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
  • *Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
Responsibilities
  • At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.
  • As a Staff AI/ML Future Sensing Engineer in the Embodied AI organization, you will serve as a senior individual contributor driving end-to-end technical work that informs next-generation sensing architecture decisions. You will help define and evaluate machine learning and perception solutions that directly impact autonomous driving performance, with emphasis on future sensing architectures, multi-modal sensor fusion, system integration, and the technical evidence required to support sensor and compute decisions.
  • In this role, you will partner closely with cross-functional engineering teams, contribute to core technical direction within your domain, and support the growth of engineers through technical collaboration and mentorship. You will help translate research into scalable onboard ML and perception solutions while contributing to the continuous improvement of GM's autonomy stack and sensing strategy.
  • *What You'll Do
  • Design and implement AI/ML solutions aligned with GM's autonomous driving and future sensing objectives
  • Lead end-to-end technical studies across sensor selection, sensor configuration, sensor placement, and multi-modal sensor fusion using cameras, lidar, radar, and related sensing modalities
  • Architect and evaluateperceptionmodels and pipelines for detection, reconstruction, tracking, localization support, semantic labeling, and uncertainty estimation
  • Drive definition of robust model-level and system-level metrics used to compare sensor configurations, quantify subsystem differences, and evaluate performance parityrelativeto existing architectures
  • Lead model development efforts spanning data curation, training, validation, performance optimization, debugging, and deployment-oriented analysis
  • Partner with simulation teams to define synthetic-data and sensor-model requirements needed to evaluate future sensing concepts under adverse weather, sensor noise, occlusions, clutter, and near-field versus long-range scenarios
  • Drive system integration thinking across sensing, calibration, compute, software architecture, and vehicle constraints
  • Translate ambiguous architecture questions into concrete experiments, technical recommendations, and clear go / no-go evidence packages
  • Design and build efficient infrastructure, pipelines, and tooling to support large-scale data processing, model training, evaluation, and rapid iteration across teams
  • Drive technical execution from prototyping through integration and readiness for production adoption, documentinglearningsand best practices
  • Support and mentor engineers through technical collaboration and code reviews, fostering knowledge sharing and engineering excellence.
  • *Your Skills & Abilities
  • Bachelor's, Master's, or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
  • Strong experience building and scaling AI/ML systems forperception, autonomy, robotics, or related real-world systems
  • Deep hands-on experience with modern deep learning frameworks such asPyTorchand strongproficiencyin Python
  • Experience working with model training pipelines, large-scale data workflows, and infrastructure enabling efficient model iteration across teams
  • Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark
  • Strong experience with model validation, debugging, performance optimization, and error analysis under real-world constraints and timelines
  • Strong experience with multi-modal sensor fusion andperceptionpipelines using cameras, radar, lidar, or related sensing modalities
  • Experience defining metrics and evaluation methodologies forperceptionor autonomy systems
  • Strong communicationskills enabling effective collaboration across engineering teams
  • Experience deploying or preparing ML models for production environments and understanding end-to-end deployment workflows.
View posting →
Lead Data Science Engineer HCSC · Helena, MT Senior Doctorate 2026-06-04
Requirements
  • Bachelor degree and 5 years of work experience in a computer science, engineering, or related field OR Master's degree and 4 years of work experience in a computer science, engineering, or related field OR Ph.D. and 2 years of work experience in a computer science, engineering, or related field"
  • Learning and growth mindset.
  • Customer-focused.
  • Interpersonal, verbal and written communication skills.
  • Must demonstrate proficiency in at least five and mastery in one of the following six areas: data analysis and relational-style query languages; data pipelining and ETL; working with semi structured and unstructured data; a high- level programming language; distributed computing; understanding of healthcare.
  • Proficiency in iterative development practices.
  • Independently delivering or leading the delivery of data engineering solutions for multiple complex analytics or data science projects and products.
  • A track record of independently delivering or leading the delivery of ML engineering capabilities.
  • Experience in Python-based Data Science frameworks (LangChain, LangGraph, LangFuse).
  • Experience in Model evaluation and deployment.
  • Experience in data curation, prep, training, and fine-tuning of Models.
  • Experience in evaluation frameworks
  • Experience in prompt engineering
  • Experience in working with multiple Models
Preferred
  • Master degree in a computational field, or Bachelor degree with significant healthcare experience
  • Understanding PySpark / Databricks to efficiently work with large data sets
  • Azure Cloud Infrastructure / Deployment with emphasis on AI related tooling, Azure ML, Azure OpenAI, etc.
  • Experience in Observability Frameworks and Framework Operationalization.
  • Experience in creation of knowledge graph database (neo4J)
  • Experience in working with Small Language Models or custom Models
  • *Are you being referred to one of our roles? If so, ask your connection at HCSC about our Employee Referral process!
Responsibilities
  • This position is responsible for the engineering work necessary for successful creation, deployment and managing of AI capabilities of the Intelligent Delivery Platform. This includes
  • ensuring data quality,
  • creation of new data pipelines,
  • optimization and management of existing data pipelines,
  • ingestion and curation of data sources for Gen AI purposes (including chunking/embedding strategies for RAG system),
  • AI Agent delivery,
  • Prompt Engineering,
  • selection and configuration of AI-specific tools and platforms
  • management and monitoring of AI models through MLOps tools and model ops practices.
  • To operationalize AI capabilities, they will work closely with larger team who will supplement where traditional application development support is needed.
  • *NOTE: This hybrid role can be located in CHICAGO IL; WAUKEGAN, IL; TULSA, OK; HELENA, MT; ALBUQUERQUE, NM; or RICHARDSON, TX ~ relocation will not be offered; sponsorship is not available.
View posting →
Machine Learning Engineering Manager Indeed · Seattle, WA Manager Doctorate 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 posting →
Senior Machine Learning Engineer Indeed · Seattle, WA Senior Doctorate 2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View posting →
Machine Learning Engineering Manager Indeed · Portland, OR Manager Doctorate 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 posting →
Senior Machine Learning Engineer Indeed · Portland, OR Senior Doctorate 2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View posting →
Machine Learning Engineering Manager Indeed · Boise, ID Manager Doctorate 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 posting →
Senior Machine Learning Engineer Indeed · Boise, ID Senior Doctorate 2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View posting →
Staff Data Scientist Micron Technology, Inc. · Boise, ID Senior Doctorate 2026-06-03
Requirements
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field, plus 5+ years of experience in data science, machine learning, or advanced analytics roles.
  • Strong proficiency in Python and SQL, with hands-on experience developing, testing, and deploying predictive or statistical models on large, complex datasets.
  • Working knowledge of core data science and AI/ML tools, including Python libraries such as pandas, NumPy, and scikit-learn, with hands-on experience in Snowflake, Streamlit, and modern AI/ML development environments.
  • Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning, actuals-to-forecast reconciliation, or financial waterfall reporting.
  • Experience partnering with Finance stakeholders and cross-functional teams to deliver scalable, user-adopted solutions, and providing technical leadership or mentorship to data scientists and analysts.
Preferred
  • Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, Mathematics, Operations Research, Finance, Economics, or a related quantitative discipline.
  • Experience applying advanced machine learning, time series modeling, optimization, or AI techniques to Finance-related data, workflows, and business needs, including corporate finance, P&L, manufacturing cost data, forecasting, scenario modeling, driver analysis, or decision support.
  • Hands-on experience developing, deploying, and monitoring conversational AI agents or LLM-based solutions in Snowflake, cloud, or similar enterprise data environments, including prompt/instruction design, evaluation, and performance optimization.
  • Experience translating finance business logic into production-grade analytical applications, model features, prompts, rules, or agent workflows that support scalable decision-making.
  • Experience with data visualization and basic UI development, including creating intuitive dashboards, analytical interfaces, or lightweight front-end experiences that improve how Finance users interact with models, insights, and AI-enabled solutions.
  • The US base salary range that Micron Technology estimates it could pay for this full-time position is:
  • $123,000.00 - $290,000.00 a yea
  • Additional compensation may include benefits, bonuses and equity.
  • Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target base pay for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. 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.
  • As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits .
Responsibilities
  • Lead the development of predictive models for finance use cases, including:
  • Forecasting (revenue, expenses, cost drivers)
  • Variance analysis (actuals vs. plan, drivers of deviation)
  • Scenario modeling and sensitivity analysis to support business planning
  • Build and implement scalable, production-grade analytical models that integrate with enterprise finance systems and data platforms
  • Develop, test, and deploy intelligent agents in a Snowflake environment, including:
  • Agent-based workflows for finance analytics use cases
  • Prompt design, evaluation frameworks, and performance testing
  • Monitoring and continuous improvement of agent outputs
  • Partner closely with Finance business stakeholders, Data Engineering, and UX teams to:
  • Translate business problems into data science solutions
  • Define success metrics and validate model performance
  • Drive adoption of analytics and AI capabilities
  • Build and optimize data pipelines and modeling workflows to clean, combine, and analyze vast, detailed data compilations from multiple sources
  • Lead exploratory analysis and prototype development to identify new opportunities for automation, insight generation, and decision support
  • Provide technical leadership and mentorship to junior data scientists, setting best practices for modeling, experimentation, and product ionization
View posting →
Machine Learning Engineering Manager Indeed · Helena, MT Manager Doctorate 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 posting →
Senior Machine Learning Engineer Indeed · Helena, MT Senior Doctorate 2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View posting →
Associate Director, Data Science Chewy Inc. · Bellevue, WA Director Doctorate 2026-06-03
Requirements
  • Apply advanced mathematics and data science methodologies;
  • Standard machine learning and statistical techniques including predictive models (time series, regression, etc.), classification, forecasting; and
View posting →
Senior Staff Research Data Scientist, DevIE Google · Kirkland, WA Senior Doctorate 2026-06-03
Requirements
  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
Preferred
  • 12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.
Responsibilities
  • Our mission is to accelerate Google's velocity by empowering developers with AI-ready knowledge, trusted content, and scaled and targeted enablement programs.
  • We are looking for a Data Scientist (DS) who can work in a rapidly evolving tech landscape with novel methodologies, to generate actionable insights for product teams and leaders.
  • In this role, you will engage deeply with Google DeepMind and the core of Google's AI capabilities. You will shape the investigative directions and strategies for Gemini, revealing actionable insights into how it integrates with Google's complex software engineering ecosystem. Additionally, you will drive an understanding of how various agentic capabilities affect software and model development workflows, leveraging these insights to optimize complex systems at a Google scale.
  • The US base salary range for this full-time position is $262,000-$365,000 + 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/) .
  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  • 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 posting →
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