Remote job
Data Scientist: Product
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About this role
Role overview Help product and operations teams understand how people use digital health benefits and where the experience can improve. You’ll establish the metrics and data models behind key journeys such as plan shopping, enrollment, reimbursements, and ongoing benefit use, then turn findings into product recommendations.
Responsibilities - Partner with product and operations colleagues to answer questions and inform priorities. - Define and maintain product measures, from company-wide outcomes to feature performance. - Analyze user journeys, engagement, and operational data to find friction and opportunities. - Design and evaluate experiments that measure the effect of product changes. - Build and maintain dbt models, metrics, dashboards, and analytical tools. - Improve data quality, event instrumentation, and self-service analytics so teams can make informed decisions.
Requirements - Experience using analytics, data science, and experimentation to influence product decisions. - Strong SQL skills and experience with dbt or a similar data transformation tool. - Experience creating analytical data models and dashboards with BI or visualization tools. - Proficiency in Python for analysis, experimentation, or statistical modeling. - Strong product judgment and the ability to explain complex findings as clear recommendations. - Comfortable working independently, navigating ambiguity, and collaborating across teams.
Nice to have Experience shaping product roadmaps through data; developing experimentation practices, including guardrail measures or sample-size guidance; analyzing funnels, cohorts, retention, or engagement; or building models for segmentation, forecasting, propensity, or recommendations. Experience in healthcare, fintech, or another regulated industry is a plus.
Tools and work setup The role uses Snowflake, SQL, and dbt for data work; Omni and Hex for analytics; Python; and GitHub with CI/CD. Familiarity with event instrumentation and application source data, such as data from Ruby on Rails systems, is helpful. The position does not work directly in the application layer day to day.