Principal Data Scientist

Azurity Pharmaceuticals is a privately held, specialty pharmaceutical company that focuses on innovative products that meet the needs of underserved patients. As an industry leader in providing unique, accessible, and high-quality medications, Azurity leverages its integrated capabilities and vast partner network to continually expand its broad commercial product portfolio and robust late-stage pipeline. The company’s patient-centric products span the cardiovascular, neurology, endocrinology, gastro-intestinal, institutional, and orphan markets, and have benefited millions of patients. For more information, visit www.azurity.com.

Azurity Pharmaceuticals is proud to be an inclusive workplace and an Equal Opportunity Employer. Azurity's success is attributable to our incredibly talented, dedicated team that focuses on benefiting the lives of patients by bringing the best science and commitment to quality into everything that we do. We seek highly motivated individuals with the dedication, integrity, and creative spirit needed to thrive in our organization.

Team Overview

Azurity Pharmaceuticals is seeking a Principal Data Scientist to lead the design, strategic development and operationalization of advanced analytics and AI/Machine Learning solutions that directly drive commercial impact across our portfolio. This is a high-visibility, high-impact role that combines hands-on data science leadership with strategic influence, helping to shape the future of commercial analytics at Azurity.

You will serve as a hands-on technical contributor and scientific thought leader across a range of innovative machine learning, statistical modeling, causal inference, and decision optimization models. These models will power initiatives across field sales, omnichannel marketing, HCP engagement, and strategic account management—You will work in close collaboration with data engineering, business strategy, field operations, and executive stakeholders to translate business objectives into deployable, scalable models that optimize brand performance and patient access.

The ideal candidate is not only a deep expert in applied data science but also a forward-thinking leader with a track record of driving business value through scalable AI systems, mentoring teams, and setting long-term analytics direction. 

Key Responsibilities

• Set the strategy and lead the execution of Azurity’s commercial analytics and AI roadmap, aligning data science initiatives with corporate growth 
• Own the end-to-end development lifecycle for machine learning and causal inference models that inform:
• HCP engagement strategies
• Omnichannel marketing targeting and optimization
• Pharmacy/channel performance optimization
• Strategic account prioritization
• Design and implement causal modeling frameworks (e.g., uplift modeling, counterfactuals, quasi-experiments), Observational causal inference techniques, including Propensity Score Matching (PSM), inverse probability weighting, and doubly robust estimators to quantify true business impact
• Drive adoption of best practices in model governance, MLOps, reproducibility, and documentation using tools like Git, DBT, MLflow, and Azure
• Serve as a technical mentor and team leader, guiding junior and senior scientists and elevating standards in modeling rigor, code quality, and business alignment
• Collaborate cross-functionally with Commercial Strategy, Marketing, Field Operations, and Executive Leadership to frame problems as scalable modeling solutions
• Influence platform and tooling decisions, with a focus on Azure-based infrastructure, Palantir Foundry, and CRM integration (Salesforce)
• While experience in causal inference modelling and forecasting applied to life science companies is preferred, those with experience in statistical, econometric, and epidemiologic impact modelling and team management expertise are strongly encouraged to apply.

Required Qualifications

• Advanced degree (PhD or MS) in a quantitative field such as Statistics, Data Science, Applied Mathematics, Engineering, or a related STEM discipline
• 7+ years of applied experience in data science,  advanced analytics, machine learning or AI roles, including experience in the pharmaceutical or life scienc