Data Scientist – Healthcare

AssistRx

Data Scientist role for healthcare analytics in specialty pharmacy hub services managing key performance indicators. Collaborating closely with Director and peer Data Scientists on analytical contributions.

Posted 5/18/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

CloudNumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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**

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythonRcohort analysissurvival analysisfunnel decompositionregression modelingdistribution-based metricsA/B testingstatistical methods

Soft Skills

written communicationverbal communicationattention to detailorganizational skillsability to explain findings