Lead Data Scientist - Commercial (Seaport MA)

EMD Serono•Boston, MA

10d•Onsite

About The Position

At EMD Serono, data drives everything we do to bring innovative medicines to patients faster. As a Lead Data Scientist, you will shape commercial and medical strategies by analyzing complex datasets and applying advanced analytics and machine learning to generate actionable insights that optimize decisions, uncover opportunities, and improve patient outcomes.

Requirements

Master’s degree in Statistics, Data Science, Mathematics, Physics, Econometrics, Operations Research, a related quantitative field, or equivalent work experience.
4+ years of experience as a data scientist in a commercial setting (pharma preferred).
Strong expertise in supervised/unsupervised learning, causal inference, hypothesis testing, scalable ML pipelines, and feature engineering.
Proficiency in Python (pandas, scikit-learn), SQL, Git, Linux, AWS; experience with large healthcare datasets (claims data a plus) and parquet files.
Experience deploying Python-based machine learning models in production using containers and/or shell scripting.
Solid business acumen and ability to prioritize high-impact problems aligned with strategic objectives.
Strong communication skills with the ability to translate analytical findings into actionable recommendations.
Proven ability to collaborate effectively across Commercial, Medical, and IT teams.
Experienced in mentoring and guiding junior data scientists in advanced techniques and best practices.

Nice To Haves

6 or more years of work experience as a data scientist in a commercial setting (pharma preferred) with a Master’s degree, or
4+ years with a PhD degree.
Prior experience with marketing mix models (especially in pharma).
US healthcare and pharma commercial expertise strongly preferred.
Demonstrated ability to leverage genAI tools and techniques for extracting features from text in a commercial context.

Responsibilities

Collaborate Across Teams: Partner with Commercial, Medical, and IT teams to identify high-impact problems and deliver analytics solutions aligned with business goals.
Lead Advanced Analytics: Design, validate, and interpret supervised (regression, classification) and unsupervised models (clustering, dimensionality reduction) to drive decision-making and identify new opportunities.
Causal Inference Expertise: Apply causal inference to experimental and observational data to optimize strategy and resource allocation.
Scalable AI/ML Solutions: Build scalable AI/ML pipelines for large, high-dimensional datasets.
Mentorship and Leadership: Mentor junior data scientists and foster a culture of excellence.
Healthcare Expertise: Leverage deep knowledge of US healthcare and pharma commercial landscapes, including claims, EMR data, to deliver impactful solutions.
Communication and Influence: Translate complex analytical findings into clear, actionable business recommendations for diverse stakeholders.