Data Scientist – Healthcare

Role Overview

• Design and execute ad hoc and recurring analyses for ITA client engagements, covering six defined families of KPIs
• Build and maintain analytical models within the six KPI families — from patient outcomes through data quality — ensuring consistent definitions, reproducible methodology, and appropriate statistical rigor
• Develop cohort analyses, funnel decompositions, survival curves, regression models, and distribution-based performance metrics that surface actionable insights within program data
• Identify trends, anomalies, and comparative performance differentials across programs, payors, geographies, and time periods; frame findings as hypotheses with supporting evidence
• Contribute to quarterly business review (QBR) preparation, including data pulls, visualization development, and narrative drafting under the direction of the Director / VP
• Produce clean, client-ready analytical exhibits — charts, tables, and written summaries — formatted for manufacturer audiences including market access leadership and patient services teams
• Participate in select client meetings as a technical resource; communicate methodology and findings clearly to non-technical stakeholders
• Define analytical specifications and prototype outputs for validated insights; partner with the dedicated BI and report development team to translate ITA analytical work into productized ThoughtSpot and Power BI dashboards — ITA owns the logic, acceptance criteria, and narrative framing; the report development team handles production build
• Maintain clear documentation of analytical methodologies, data transformations, and code to support reproducibility and team knowledge management
• Surface upstream data quality issues that affect insight reliability; partner with data governance teams on remediation
• Contribute to the evolution of the ITA analytical framework as new client engagements reveal novel questions and additional KPI families emerge
• Stay current on emerging methods in healthcare analytics, specialty pharmacy data, and applied machine learning relevant to program performance and patient journey analysis

Requirements

• Approximately 5 years of experience in healthcare analytics, with direct experience in one or more of the following: pharmaceutical manufacturer (commercial, market access, or patient services analytics), pharma consulting, health insurer, or pharmacy benefit manager (PBM)
• Strong proficiency in SQL; experience querying and manipulating data in cloud data warehouse environments (Snowflake preferred)
• Python or R required; Python preferred (pandas, numpy, scipy, and scikit-learn)
• Working knowledge of statistical methods applicable to program performance analysis: cohort analysis, survival analysis, funnel decomposition, regression modeling, distribution-based metrics, and experimental design and A/B testing frameworks
• Experience producing structured, audience-ready analytical outputs — not just raw analyses; strong attention to how findings are communicated, not just computed
• Clear, organized written and verbal communication skills; ability to explain quantitative findings in plain language
• Bachelor's degree in a quantitative field (statistics, mathematics, data science, computer science, economics, or related); advanced degree a plus

Tech Stack

• Cloud
• Numpy
• Pandas
• Python
• Scikit-Learn
• SQL

Benefits

• Supportive, progressive, fast-paced environment
• Competitive pay structure
• Matching 401(k) with immediate vesting
• Medical, dental, vision, life, & short-term disability insurance
• Opportunity to impact patient outcomes through data-driven healthcare technology.
• Collaborative and mission-driven culture that values innovation and continuous learning.
• Access to cutting-edge cloud technologies and modern data engineering tools.
• Competitive compensation, comprehensive benefits, and career growth opportunities**