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.
Design, develop, and deploy predictive models and analytical solutions using Dagster/Airflow and DBT workflows to drive data-informed market access and pricing decisions.
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.

Requirements

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
Advanced proficiency in Python or R for statistical modeling, machine learning, and data analysis
Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) and predictive modeling techniques
Hands-on experience with workflow orchestration platforms (Dagster, Airflow, Prefect, or similar)
Proficiency in SQL for complex data manipulation and working with relational databases
Expertise in data visualization tools (Tableau, Power BI, or similar) and creating executive-level dashboards
Experience with cloud platforms (Kubernetes) and modern data stack technologies
Strong foundation in statistical methods, experimental design, and A/B testing
Understanding of MLOps principles and model deployment best practices
Deep understanding of pharmaceutical market access, pricing strategies, and reimbursement dynamics
Experience analyzing longitudinal patient data, claims data, and formulary datasets
Working knowledge of the US healthcare system, payer landscape, and regulatory environment
Familiarity with healthcare data standards (e.g., NDC, HCPCS, ICD codes, IQVIA)

Benefits

high-quality healthcare
prevention and wellness programs
at least 14 weeks’ gender-neutral parental leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

predictive modelingmachine learningstatistical analysisdata analysisdata visualizationworkflow orchestrationdata manipulationexperimental designA/B testingcloud platforms

Soft skills

communicationcollaborationproblem-solvingstrategic thinkingdata storytellingleadershipcross-functional partnershipanalytical thinkingstakeholder engagementadaptability