Healthcare Data Scientist - KPI Analytics

AssistRx; New York (NY); On-site; USD 105,000 - 134,000; Full time

Job summary

AssistRx is seeking a Data Scientist, ITA to be a primary analytical contributor within a small, high-performance team. You will design and execute analytical models, generate KPI insights, and help build client-facing outputs, including pilot QBR materials and dashboard prototypes.

The role requires strong SQL and Python, familiarity with statistical methods for program performance analysis, and the ability to communicate findings to non-technical stakeholders.

Qualifications

• 5 years of healthcare analytics experience in pharma, pharma consulting, health insurer, or PBM
• Strong SQL; cloud data warehouse experience (Snowflake preferred)
• Python or R required; Python preferred (pandas, numpy, scipy, scikit-learn)
• Statistical methods for program performance analysis: cohort, survival, funnel, regression, distribution-based metrics, A/B testing
• Experience producing structured, audience-ready analytical outputs and clear communication

Responsibilities

• Analytical Execution across six KPI families
• Build and maintain analytical models and ensure reproducible methodology
• Develop cohort analyses, survival curves, regressions, and distribution-based metrics
• Create client-ready exhibits and visualizations for QBRs
• Translate methodology and findings to non-technical stakeholders
• Prototype and productize insights with ThoughtSpot and Power BI dashboards

Skills

SQL proficiency

Python

Statistics methods

Communication

Education

Bachelor's degree in quantitative field

Tools

Snowflake

ThoughtSpot

Power BI

dbt

Job description

AssistRx is seeking a Data Scientist, ITA to be a primary analytical contributor within a small, high-performance team. You will design and execute analytical models, generate KPI insights, and help build client-facing outputs, including pilot QBR materials and dashboard prototypes.

The role requires strong SQL and Python, familiarity with statistical methods for program performance analysis, and the ability to communicate findings to non-technical stakeholders.