Data Scientist - HOS Analytics

Summary

Alignment Health is a data and technology-driven healthcare company focused on improving care delivery and clinical outcomes for seniors. The Data Scientist will analyze Health Outcomes Survey data, model member health trajectories and HOS performance drivers, and develop targeted interventions to improve Medicare Star Ratings. The role also involves building analytical pipelines, dashboards, and models in collaboration with clinical, engineering, compliance, and survey vendor teams.

Responsibilities

• Collaborate with Stars, clinical, and care management leaders to understand HOS performance drivers and translate them into analytical solutions
• Segment members by likelihood to respond to the HOS survey and by predicted physical or mental health trajectory, to prioritize outreach and intervention
• Build and fine-tune models predicting member-level risk of HOS composite decline, including Improving/Maintaining Physical Health, Improving/Maintaining Mental Health, Monitoring Physical Activity, and Reducing the Risk of Falling
• Analyze item-level HOS survey data, not just composite scores, to isolate which specific survey questions are driving measure performance
• Build pipelines that track HOS survey administration cycles — baseline and follow-up cohorts, sampling, fielding, and response rates — and validate case-mix adjustment logic against CMS methodology
• Model statistical significance and year-over-year variance to distinguish genuine performance shifts from survey noise or sampling error
• Coordinate with HOS survey vendors on cohort tracking, sampling methodology, fielding timelines, and case-mix adjustment specifications
• Collaborate with engineering teams to version, test, and deploy models using Git, CI/CD pipelines, and virtual machine (VM) environments
• Partner with clinical, care management, complex case management, Compliance, and Legal teams to ensure HOS-related data outputs and interventions align with CMS guidance
• Build dashboards tracking measure-level HOS performance against Star Rating cut points and prior-year trend for each composite
• Help standardize definitions, documentation logic, and reporting workflows to scale HOS analytics enterprise-wide

Skills

• 2+ years of relevant experience in predictive modeling and analysis, with demonstrated application to longitudinal or outcomes-based member data
• Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• Demonstrated experience with CMS HOS survey methodology, including baseline/follow-up cohort design, case-mix adjustment, and item response theory or other psychometric methods
• Working knowledge of individual HOS composite measures: Improving/Maintaining Physical Health, Improving/Maintaining Mental Health, Monitoring Physical Activity, and Reducing the Risk of Falling
• Working knowledge of CMS Star Ratings procedures, including how HOS measures are weighted, cut-point determined, and incorporated into the overall Star Rating
• Excellent communication, analytical, and collaborative problem-solving skills
• Experience building end-to-end data science solutions and applying machine learning methods to real-world problems with measurable outcomes
• Solid data structures and algorithms background
• Strong programming skills in one of the following: Python, Java, R, Scala, or C++
• Demonstrated proficiency in SQL and relational databases
• Experience with data visualization and presentation, turning complex longitudinal outcomes analysis into clear, actionable insight for non-technical stakeholders
• Experience setting experimental or analytical frameworks for complex, ambiguous scenarios, including longitudinal/cohort study design
• Understanding of relevant statistical measures such as confidence intervals, significance of error measurement, and development/evaluation data sets
• Experience manipulating and analyzing complex, high-volume, high-dimensionality, and unstructured data from varying sources
• PhD highly desired
• Healthcare experience, particularly within Medicare Advantage
• Experience with functional status, frailty, or geriatric outcomes modeling
• Experience in cloud ecosystems such as Azure or AWS
• Published work in academic conferences or industry circles related to survey methodology, psychometrics, or health outcomes measurement
• Demonstrable track record of handling ambiguity, prioritizing needs, and delivering results in an agile, dynamic environment

Qualifications

Must Haves

• 2+ years of relevant experience in predictive modeling and analysis, with demonstrated application to longitudinal or outcomes-based member data
• Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• Demonstrated experience with CMS HOS survey methodology, including baseline/follow-up cohort design, case-mix adjustment, and item response theory or other psychometric methods
• Working knowledge of individual HOS composite measures: Improving/Maintaining Physical Health, Improving/Maintaining Mental Health, Monitoring Physical Activity, and Reducing the Risk of Falling
• Working knowledge of CMS Star Ratings procedures, including how HOS measures are weighted, cut-point determined, and incorporated into the overall Star Rating
• Excellent communication, analytical, and collaborative problem-solving skills
• Experience building end-to-end data science solutions and applying machine learning methods to real-world problems with measurable outcomes
• Solid data structures and algorithms background
• Strong programming skills in one of the following: Python, Java, R, Scala, or C++
• Demonstrated proficiency in SQL and relational databases
• Experience with data visualization and presentation, turning complex longitudinal outcomes analysis into clear, actionable insight for non-technical stakeholders
• Experience setting experimental or analytical frameworks for complex, ambiguous scenarios, including longitudinal/cohort study design
• Understanding of relevant statistical measures such as confidence intervals, significance of error measurement, and development/evaluation data sets
• Experience manipulating and analyzing complex, high-volume, high-dimensionality, and unstructured data from varying sources

Nice to Haves

• PhD highly desired
• Healthcare experience, particularly within Medicare Advantage
• Experience with functional status, frailty, or geriatric outcomes modeling
• Experience in cloud ecosystems such as Azure or AWS
• Published work in academic conferences or industry circles related to survey methodology, psychometrics, or health outcomes measurement
• Demonstrable track record of handling ambiguity, prioritizing needs, and delivering results in an agile, dynamic environment

Benefits

• Fully Remote
• Ample room for growth and innovation