Data Scientist, ITA

AssistRx, Inc.; New York (NY); On-site; USD 105,000 - 134,000; Full time

Job summary

AssistRx, Inc. is seeking a Data Scientist for ITA who will design and execute analytical models and deliver insights across KPI families. You will build audience-ready outputs and contribute to client-facing materials, working closely with senior leadership and two peer Data Scientists.

The role emphasizes SQL/Python depth, statistical methods for program performance, and clear communication to stakeholders in pharma and health services. Prior pharma or PBM experience is required or preferred.

Qualifications

• Bachelor's degree in a quantitative field; advanced degree a plus.
• Approximately 5 years of experience in healthcare analytics.
• Strong proficiency in SQL; experience querying and manipulating data in cloud data warehouses (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; focus on communicating findings clearly.
• Familiarity with pharmaceutical hub program workflows and specialty pharmacy data structures is preferred.
• Experience with ThoughtSpot or Power BI preferred; exposure to generative AI in analytics workflows is a plus.

Responsibilities

• Analytical Execution: design and execute ad hoc and recurring analyses for ITA client engagements, covering six KPI families.
• Build and maintain analytical models within the six KPI families, ensuring reproducible methodology and statistical rigor.
• Develop cohort analyses, survival curves, regression models, and distribution-based metrics to surface actionable insights.
• Identify trends, anomalies, and differential performance 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 for the Director/VP.
• Produce client-ready analytical exhibits (charts, tables, and written summaries) formatted for manufacturer audiences including market access leadership.
• Partner with BI/report development to translate ITA analyses into productized ThoughtSpot and Power BI dashboards; own logic and narrative framing.
• Maintain clear documentation of methodologies, data transformations, and code to support reproducibility.
• Surface upstream data quality issues and collaborate with data governance on remediation.

Skills

SQL

Python

R

Cohort analysis

Survival analysis

Funnel decomposition

Regression modeling

A/B testing

Education

Bachelor's degree in a quantitative field

Advanced degree a plus

Tools

Snowflake

Power BI

ThoughtSpot

dbt

Job description

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 /Yr.