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About the Role
The Data Scientist, ITA will be a primary analytical contributor within a small, high-performance team. Working directly alongside the Director / VP and two peer Data Scientists, this individual will own the design and execution of analytical models, generate program insights across key KPI families, and help build the client-facing outputs that define the ITA value proposition. The role requires technical depth in SQL and Python, working familiarity with statistical methods, and an orientation toward clear, audience-appropriate communication. Experience in pharma, pharma consulting, at a health insurer, or at a PBM is required.
Responsibilities
- 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.
- Produce clean, client-ready analytical exhibits (charts, tables, and written summaries) formatted for manufacturer audiences.
- 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 dashboards.
- 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.
- Familiarity with pharmaceutical hub program workflows, including case management, prior authorization, benefits verification, payor adjudication, and patient financial assistance programs.
- Experience working with specialty pharmacy data structures and source systems (CRM, pharmacy dispensing platforms, benefits verification systems).
- Background in patient access or market access analytics at a pharmaceutical manufacturer, including program KPI development and payor-level performance analysis.
- Analytical experience at a health insurer or PBM, particularly in formulary analytics, specialty drug utilization, or patient access reporting.
- Experience with ThoughtSpot or Power BI preferred.
- Exposure to or curiosity about generative AI and its applications in analytics workflows (natural language querying, entity resolution, or automated insight generation).
- Experience contributing to a client-facing analytics product or repeatable analytical framework.
- Familiarity with dbt or similar data transformation frameworks.
Skills
- SQL
- Python
- R
- pandas
- numpy
- scipy
- scikit-learn
- Cohort analysis
- Survival analysis
- Funnel decomposition
- Regression modeling
- Distribution-based metrics
- Experimental design
- A/B testing
- ThoughtSpot
- Power BI
- dbt
Location
- Remote
Work Type
- Full-time
Experience Level
- 5 years of experience in healthcare analytics
Education Level
- Bachelor's degree in a quantitative field
Salary/Compensations
- USD $105,000.00 - USD $133,500.26 /Yr.