Associate Director, Data Science - Market Access

Job Title: Associate Director, Data Science - Market Access

Location: Cambridge, MA, Morristown, NJ

About the Job

Join the team transforming care for people with immune challenges, rare diseases, cancers, and neurological conditions. In Specialty Care, you’ll help deliver breakthrough treatments that bring hope to patients with some of the highest unmet needs.

Join Sanofi in one of our US Market Access Shared Services functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world. Work collaboratively with matrix partners to manage the strategic attainment of product access and appropriate reimbursement at key customers by participating in and overseeing the negotiation process of financial terms, as well as documented terms and conditions, for assigned customers.

About Sanofi:
We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Main Responsibilities:

As the Associate Director of Data Science, you will lead the development and delivery of advanced analytics solutions to support market access and pricing decisions. You will perform sophisticated analyses on patient longitudinal data, develop interactive dashboards and reports, and translate complex data into actionable insights for stakeholders. Your role will involve partnering with various departments to support strategic initiatives and leveraging analytics capabilities to enhance data-driven decision-making. Core responsibilities of the role are as follows:

• Design, develop, and deploy predictive models and analytical solutions using Dagster/Airflow and DBT workflows to drive data-informed market access and pricing decisions. Hands on experience with R and/or Python is required.

• Architect and maintain scalable datasets that integrate with existing data engineering infrastructure and support cross-functional analytical needs

• Create interactive dashboards and reports using business intelligence tools that translate complex data into actionable insights for stakeholders

• Perform advanced statistical analysis on patient longitudinal data and large customer datasets to identify trends, patterns, and strategic opportunities

• Develop and implement machine learning algorithms to enhance forecasting capabilities and predictive analytics across market access functions

• Collaborate closely with the data engineering team, SQL developers, and analytics product management to ensure data quality, pipeline efficiency, and business alignment

• Serve as the technical bridge between data engineering infrastructure and business-facing analytics, ensuring seamless integration of analytical solutions

• Partner cross-functionally with Pricing, Contract Development, Value and Access, Account Management, Finance, Forecasting, and Data Management teams to drive strategic initiatives

• Communicate complex analytical findings through compelling data narratives and visualizations tailored to diverse audiences

• Continuously evaluate and implement emerging methodologies and technologies in data science to advance the team's predictive capabilities

About You

Experience:

• 5+ years of experience in data science or advanced analytics within Pharmaceutical or Payer organizations

  5+ years of hands-on experience building and deploying predictive models and machine learning solutions on large-scale datasets

• Demonstrated experience working with workflow orchestration tools (Dagster, Airflow, or similar) to productionize analytical models

• Proven track record of translating business problems into data science solutions that drive measurable outcomes

• Experience collaborating with data engineering teams and contributing to data pipeline development

Technical Skills:

• Advanced proficiency in Python or R for statistical modeling, machine learning, and data analysis<