Sanofi is seeking an Associate Director of Data Science in Market Access to lead the development of advanced analytics solutions aimed at improving product access and reimbursement strategies in the pharmaceutical sector. The ideal candidate will possess extensive experience in data science, particularly within pharmaceutical or payer organizations, and will be responsible for translating complex data into actionable insights
Job Summary
Lead the development and delivery of advanced analytics solutions to support market access and pricing decisions.
Design, develop, and deploy predictive models and analytical solutions using Dagster/Airflow and DBT workflows.
Collaborate cross-functionally with Pricing, Contract Development, Value and Access, Account Management, Finance, Forecasting, and Data Management teams.
Matching Summary
Match Score: 85
Sanofi is seeking an Associate Director of Data Science in Market Access to lead the development of advanced analytics solutions aimed at improving product access and reimbursement strategies in the pharmaceutical sector. The ideal candidate will possess extensive experience in data science, particularly within pharmaceutical or payer organizations, and will be responsible for translating complex data into actionable insights.
Salary
Base: $148,500.00 - $214,500.00; Bonus/Equity: Not specified; Benefits: Included
Skills & Requirements
Must-have
predictive models and analytical solutions
patient longitudinal data analysis
interactive dashboards and reports
Python or R for statistical modeling
workflow orchestration tools (Dagster, Airflow)
SQL for complex data manipulation
pharmaceutical market access and pricing
Nice-to-have
AI-powered biopharma company
transforming care for people with immune challenges
data-driven decision-making
emerging methodologies and technologies
Key Requirements
5+ years of experience in data science or advanced analytics
5+ years of hands-on experience building predictive models
Experience with workflow orchestration tools
Experience collaborating with data engineering teams