Data Scientist – HOS Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with Stars, clinical, and care management leaders to comprehend HOS performance drivers and convert them into analytical solutions.

• Segment members based on their likelihood to engage with the HOS survey and forecast physical or mental health trajectories to prioritize outreach and intervention efforts.

• Develop and refine models that predict member-level risk of HOS composite decline.

• Analyze item-level HOS survey data to pinpoint survey questions that influence measure performance.

• Create pipelines that track HOS survey administration cycles, cohorts, sampling, fielding, and response rates.

• Validate case-mix adjustment logic in accordance with CMS methodology.

• Model statistical significance and year-over-year variance to differentiate performance shifts from survey noise or sampling errors.

• Coordinate with HOS survey vendors regarding cohort tracking, sampling methods, fielding timelines, and case-mix adjustment specifications.

• Collaborate with engineering teams to version, test, and deploy models utilizing Git, CI/CD pipelines, and VM environments.

• Partner with clinical, care management, Compliance, and Legal teams to ensure outputs and interventions align with CMS guidance.

• Construct dashboards that monitor measure-level HOS performance against Star Rating thresholds and trends from prior years.

• Standardize definitions, documentation logic, and reporting workflows for enterprise-wide HOS analytics.

⛳️ Requirements

• A minimum of 2 years of relevant experience in predictive modeling and analysis, with proven application to longitudinal or outcomes-based member data.

• Required: PhD in Computer Science, Engineering, Mathematics, Statistics, or a related field.

• Demonstrated experience with CMS HOS survey methodology, encompassing baseline/follow-up cohort design, case-mix adjustment, and item response theory or other psychometric methods.

• Familiarity with individual HOS composite measures: Improving/Maintaining Physical Health, Improving/Maintaining Mental Health, Monitoring Physical Activity, and Reducing the Risk of Falling.

• Understanding of CMS Star Ratings processes, including the weighting of HOS measures, determination of cut-points, and their incorporation into the overall Star Rating.

• Strong programming capabilities in one of the following: Python, Java, R, Scala, or C++.

• Proven expertise in SQL and relational databases.

• Experience in building comprehensive data science solutions and applying machine learning techniques to real-world problems with measurable results.

• Solid foundation in data structures and algorithms.

• Experience with data visualization and presentation techniques.

• Background in establishing experimental or analytical frameworks for complex, ambiguous scenarios, including longitudinal/cohort study design.

• Understanding of confidence intervals, error measurement significance, and development/evaluation datasets.

• Experience in manipulating and analyzing intricate, high-volume, high-dimensional, and unstructured data from diverse sources.

• Exceptional communication, analytical, and collaborative problem-solving abilities.

• Preferred: Experience in healthcare, particularly within Medicare Advantage.

• Preferred: Background in functional status, frailty, or geriatric outcomes modeling.

• Preferred: Familiarity with cloud ecosystems such as Azure or AWS.

• Preferred: Published works related to survey methodology, psychometrics, or health outcomes measurement.

• Preferred: Proven ability to manage ambiguity, prioritize needs, and achieve results in an agile, dynamic environment.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and holiday schedule.

• Opportunities for professional development and growth.

• Collaborative and inclusive work environment.