Senior Data Scientist

About the Role

Key Responsibilities

• Serve as the subject matter expert on industry databases and competitive intelligence in the design and build of the AI products and services.
• In collaboration with Pioneering Intelligence, own outcomes of tools and analyses that augment competitive intelligence and portfolio analytics across the Flagship ecosystem.
• Design, build, and iterate bespoke analyses that synthesize diverse drug pipeline and commercial datasets into strategic insights.
• Develop quantitative models for risk/value optimization using a range of statistical approaches such as Bayesian statistics, survival models, Monte Carlo simulations, and portfolio selection algorithms.
• Prototype LLM-based workflows for specialized analyses.
• Create visualizations for translating complex results into key insights.
• Curate and engineer data assets from data feeds and create data ingestion pipelines.
• Collaborate cross-functionally to develop, validate, and refine models.
• Present progress in regular research and product development meetings, prepare reports, and present findings for stakeholders and leadership.

Requirements

• PhD in statistics, biostatistics, applied mathematics, computer science, physics, computational biology, or related quantitative field with a strong statistics background.
• Fluency in Python and standard statistical analysis packages.
• Experience analyzing large-scale pharma/biotech or healthcare datasets and deriving strategic insights.
• Demonstrated skill with statistical modeling and optimization (e.g., Bayesian inference, survival analysis, Monte Carlo methods, portfolio theory).
• Familiarity with the drug development pipeline.
• Interest in LLMs and their applications.
• Demonstrated ability to collaborate in interdisciplinary teams and communicate complex technical concepts effectively.
• Ability to take initiative and work independently.
• Excellent analytical and problem-solving skills tailored to innovative computational research.

Nice to Have

• Demonstrated industry experience in applied data science enabling Competitive Intelligence across drug development portfolios (3+ years).
• Prior use of specialized competitive intelligence databases (e.g., Clarivate Cortellis, EvaluatePharma, Citeline, GlobalData, etc.).
• Experience with version control software (e.g., Git) and AWS cloud computing.
• Experience leveraging LLMs in development environments.