Job Matches
Washington job postings for occupations your coursework prepares you for. Sorted by how many of the occupation's tasks your courses cover.
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-06.
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- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
Job Summary The Senior Director, Biostatistics, provides leadership, oversight, and technical/scientific direction across multiple therapeutic areas. This role leads and develops a high-performing biostatistics team that delivers both strong scientific engagement and operational excellence thr
- PhD in Statistics or Biostatistics with 12+ years of progressive experience in the pharmaceutical or biotechnology industry, including extensive involvement in clinical research and late-stage development programs
- Minimum of 5 years of demonstrated people leadership experience, including responsibility for hiring, developing, mentoring, and performance management of biostatistics professionals
- Deep and end-to-end understanding of the clinical development process, from study design and development planning through regulatory submission (e.g., NDA/BLA) and post-submission activities
- Strong working knowledge of global regulatory and industry best practices, including protocol and SAP development, statistical interpretation, and health authority expectations
- The Senior Director, Biostatistics, provides leadership, oversight, and technical/scientific direction across multiple therapeutic areas. This role leads and develops a high-performing biostatistics t… The Senior Director, Biostatistics, provides leadership, oversight, and technical/scientific direction across multiple therapeutic areas. This role leads and develops a high-performing biostatistics team that delivers both strong scientific engagement and operational excellence throughout the clinical development lifecycle. Core responsibilities include trial design and development planning, statistical analysis strategy, modeling and simulation, regulatory submission support, advisory committee preparation, and scientific presentations.
- The Senior Director, Biostatistics plans, directs, and oversees the design, preparation, and execution of the biostatistical strategy supporting research and development, ensuring the appropriate appl… The Senior Director, Biostatistics plans, directs, and oversees the design, preparation, and execution of the biostatistical strategy supporting research and development, ensuring the appropriate application of sound statistical theory and methodologies across designated therapeutic areas. In support of Clinical Development strategy, this role provides scientific review and oversight of key development materials, including but not limited to clinical protocols, statistical analysis plans, health authority submission documents, and publication materials. External scientific engagement is a core accountability of the role, including leadership of and participation in health authority interactions.
- Operational excellence is demonstrated through the effective and efficient delivery of the Clinical Development portfolio, including resource planning, prioritization, timeline management, and functional outsourcing.
- The Senior Director serves as a senior statistical subject-matter expert and knowledge resource to cross-functional project teams and acts as a point of escalation and resolution for biostatistical is… The Senior Director serves as a senior statistical subject-matter expert and knowledge resource to cross-functional project teams and acts as a point of escalation and resolution for biostatistical issues across relevant therapeutic areas.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
At HCSC, our employees are the cornerstone of our business and the foundation to our success. We empower employees with curated development plans that foster growth and promote rewarding, fulfilling careers. Join HCSC and be part of a purpose-driven company that will invest in your professional de
- 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 fie… 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.
- 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,
- 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.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
- 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… 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
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Job Description At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world
- BS/MS in Computer Science or equivalent experience
- 6-10+ years building and shipping enterprise distributed or cloud-native systems
- Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
- Strong foundation in system design, distributed systems, and cloud architecture best practices
- At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the sc… At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
- Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly… Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
- You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'l… You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
- In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state… In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
- Production experience with Cloud and ML technologies
- Experience working in the below areas and algorithms will be ideal but not mandatory:?
- Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
- Algorithms: Transformer models, Attention mechanism, Prompt tooling
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
- 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 consi… 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 incl… 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.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
B2B SAAS data observability software.Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure r
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Overview _What You'll Be Doing_ Cadmus is seeking a Technical Project Manager (TPM) with a passion for delivering high quality projects in a complex, fast paced environment to support a major commercial client in the automotive entertainment space. You will work with machine-learning
- 5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
- Bachelor's degree in Information Systems, BI or Analytics or Engineering.
- Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
- Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
- Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals… Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
- Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing b… Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
- Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
- Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
B2B SAAS data observability software.Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure r
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Senior AI/ML Engineer Anywhere Type: Contract-to-Hire Category: Development Industry: Government Workplace Type: Remote Reference ID: JN -052026-107129 Date Posted: 05/26/2026 Shortcut: http://careers.eliassen.com/YsQ2uG + Description + Recom
- 10+ years in Software or IT with 7+ years in data analysis, AI engineering, and machine learning engineering.
- Hands-on experience with LLM orchestration, integration, and vLLM-based inference for document understanding.
- Experience with multi-agent AI systems, RAG pipelines, vector databases, and prompt engineering.
- Strong Python skills with TensorFlow and PyTorch.
- Engineer AI solutions using LLM providers and implement complex multi-agent workflows.
- Design and develop predictive models using regression, classification, clustering, and neural networks.
- Build RAG pipelines, integrate vector databases, and apply prompt engineering with LangChain or LangGraph.
- Develop end-to-end AI/ML/NLP plans compliant with cybersecurity policies.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
- As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design … As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
- You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also… You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
- Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
- Translate data into actionable insights to guide product, marketing and business decisions.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.