RequirementsPOSITION SUMMARYThe 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.
KEY RESPONSIBILITIESAnalytical 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
REQUIRED 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
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
