Overview:
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 (pilot QBR materials, trend narratives, analytical summaries, prototype of insight-focused dashboarding) that define the ITA value proposition. The role requires a combination of technical depth in SQL and Python, working familiarity with statistical methods applicable to program performance analysis, and an orientation toward clear, audience-appropriate communication. Experience in pharma, pharma consulting, at a health insurer, or at a PBM is required: this work depends on understanding how specialty programs function, how manufacturers define success, and how data from hub operations connects to the broader access and reimbursement landscape.
Responsibilities:
- Analytical Execution
-
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
-
Client-Facing Output Development
-
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
-
Productization & Documentation
-
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
-
Continuous Improvement
-
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
Qualifications:
- 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
-
(Preferred) Familiarity with pharmaceutical hub program workflows, including case management, prior authorization, benefits verification, payor adjudication, and patient financial assistance programs
-
(Preferred) 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
-
(Preferred) Analytical experience at a health insurer or PBM, particularly in formulary analytics, specialty drug utilization, or patient access reporting
-
(Preferred) Experience with ThoughtSpot or Power BI preferred
-
(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
-
(Preferred) Familiarity with dbt or similar data transformation frameworks
Pay Range: USD $105,000.00 - USD $133,500.26 /Hr.