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Data ScientistAssistRx • New York, New York, United States
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Data Scientist

AssistRx
  • US
    New York, New York, United States
  • US
    New York, New York, United States
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About

AssistRx is a specialty pharmacy hub services company that manages therapy initiation and patient access programs for pharmaceutical manufacturers. The company's flagship platform, iAssist, integrates at the point of prescribing and connects patients, providers, payors, and manufacturers across complex specialty therapy programs. Welsh, Carson, Anderson & Stowe acquired AssistRx in February 2024, and the company has grown significantly, supporting a broad portfolio of programs across therapeutic areas including oncology, immunology, rare disease, and obesity. POSITION SUMMARY
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. KEY 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 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 PREFERRED QUALIFICATIONS
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
  • New York, New York, United States

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