Data Scientist, Pharmacy (Part D Stars)
Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first.We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together.
Alignment Health care is a data and technology driven healthcare company focused partnering with health systems, health plans and provider groups to provide care delivery that is preventive, convenient, coordinated, and that results in improved clinical outcomes for seniors.
As a Data Scientist on the Pharmacy team, you’ll play a key role in evolving the analytical engine behind our pharmacy data and Part D Star measures within our Medicare Advantage line of business. This role focuses on applied data science to enhance the analytics, trending, and predictive modeling that inform pharmacy and Part D Star strategy. You'll help make tools more transparent, precise, adaptable, and actionable — incorpo-rating new methods, partnerships, and technologies along the way. Job Duties/Responsibilities:
- Partner with Pharmacy leadership to understand business problems, propose analytical solutions, and turn findings into clear, actionable takeaways for stakeholders.
- Convert analytical models and business rules into scalable, production-ready tools.
- Design dashboards and reporting that track Stars measure trajectories and intervention impact.
- Build cut-point projection and simulation models to forecast Star Rating outcomes under varying performance and CMS methodology scenarios.
- Build out prioritization rules, measure improvement models, and next-best-action (NBA) logic.
- Analyze the financial impact of pharmacy and Star performance to help leadership prioritize investment and interventions.
- Manage projects end to end – from problem definition through analysis, model building, validation, deployment support, and ongoing monitoring.
- Collaborate with data and engineering teams to version, test, and deploy models using Git, CI/CD pipelines, and virtual machine (VM) environments.
- Help standardize definitions, documentation logic, and reporting workflows to scale enterprise-wide AI-readiness.
- Bring in new data sources, techniques, and emerging tools to continuously improve analytical capabilities.
- Other duties as assigned by your manager.
Supervisory Responsibilities: N/A
MINIMUM REQUIREMENTS:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Minimum Experience:
- 2+ years of relevant experience in predictive modeling and data analysis
Education/Licensure:
- Bachelor or Master’s in Computer Science, Engineering, Mathematics, Statistics, or related field (PhD a plus), or equivalent related experience.
Other:
- Excellent communication, analytical and collaborative problem-solving skills.
- Experience in building data science solutions and applying machine learning methods to real world problems with measurable outcomes.
- Familiarity with time-series analysis or forecasting methods.
- Solid data structures & 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 analysis into insight.
- Experience in setting experiment
This role requires you to be in the United States. If that means relocating or flying in, it is worth checking fares before you commit to a start date.
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