We’re seeking a Senior Data Scientist with a passion for turning complex data into actionable insights that shape the future of healthcare. In this role, you’ll work at the intersection of advanced analytics, clinical strategy, and business innovation to develop predictive models and data products that directly inform network and provider decisions.
If you’re looking to apply your technical expertise to real-world healthcare challenges and contribute to improved outcomes across access, affordability, and equity—this is the role for you. What You’ll Be Doing
- Analyze large and diverse healthcare datasets, including claims, provider, and operational data
- Design, develop, and deploy machine learning models and statistical analyses that support strategic decision-making
- Collaborate with stakeholders across technical and non-technical teams—business leaders, clinical experts, and executives—to guide model development and ensure adoption
- Translate analytical findings into clear, compelling narratives through visualizations, reports, and presentations
- Identify gaps, challenges, and opportunities across datasets and processes, and propose effective solutions
Contribute to the documentation, testing, and ongoing improvement of analytical tools and models
Ideal Candidate Profile
Bachelor’s degree with 3+ years of experience in a quantitative field such as Data Science, Statistics, Computer Science, Engineering, Physics, or EconomicsOR Master’s degree with 2+ years of experienceOR PhD in a related disciplineOR equivalent of 7+ years relevant experience without a formal degreeProficient in at least 4 of the following 6 areas :Data analysis and SQL or similar query languagesMachine learning and statistical modelingData visualization (e.g., dashboards, charts, storytelling tools)High-level programming (e.g., Python, R, or similar)Distributed computing and big data toolsHealthcare data knowledge and industry understanding Preferred QualificationsAdvanced degree (Master’s or PhD) in a quantitative field
Experience working with large-scale healthcare data (e.g., claims, provider networks)Familiarity with end-to-end model deployment in a production environment