Data Scientist-Healthcare

Role Description: 
Purpose of the role: Improve the quality, credibility, and usefulness of our client reporting. The role brings a healthcare economics or value based care background so that what we report to clients reflects sound methodology: risk adjustment, attribution, utilization and cost trend, and defensible savings and outcomes measurement.

Key responsibilities
•Design and improve the analytics behind client reporting, including cost of care trend, utilization, program impact, and return on investment.
•Build and validate measurement methodology such as risk adjustment, cohort construction, attribution logic, and comparison group design.
•Turn analytic output into reporting that a client audience can read and trust, partnering with client facing teams on narrative and presentation.
•Document methodology so results can be explained, audited, and reproduced.
•Partner with data engineering and the data architect on the models and data assets reporting depends on.
•Investigate anomalies and questions raised by clients or internal stakeholders and close them with evidence.
Required qualifications
•5 or more years of analytics or data science experience in healthcare, with direct exposure to healthcare economics, actuarial analytics, or value based care measurement.
•Strong SQL plus Python or R for analysis and modeling.
•Working knowledge of medical and pharmacy claims data, including standard code sets and common data quality pitfalls.
•Demonstrated ability to explain methodology and findings to non technical audiences.
Preferred qualifications
•Experience with risk adjustment models, quality measure sets, or shared savings and total cost of care programs.
•Experience building client facing or externally published reporting.
•Experience working in Snowflake and with modern BI tooling."