Job Description
Data scientists generate actionable insights from datasets to optimize commercial strategies and enhance patient outcomes in pharmaceuticals. In this role, individuals analyze complex healthcare data to identify opportunities and refine processes that accelerate development of oncology, neurology, and fertility medicines.
Merck Group operates as EMD Serono, a division focused on medicines and intelligent devices across therapeutic areas. The unit teams with colleagues on six continents to support diverse clients and patients through relentless exploration and technology.
Typical tasks include partnering with commercial, medical, and IT teams to uncover high-impact problems, designing supervised and unsupervised models like regression and clustering, applying causal inference to experimental data, and building scalable AI/ML pipelines for large datasets. Professionals work on projects involving healthcare claims, EMR data, and parquet files, ensuring reliable performance. A key constraint involves escalating issues like integrating machine learning models into production using containers and shell scripting.
Compensation ranges from $111,100 to $166,700 annually. Location is Seaport MA, with no remote work specified. Schedule follows standard hours, potentially including travel. Benefits include medical, vision, and dental insurance, life and disability insurance, 401(k) with matching, paid time off, paid holidays, and incentives like bonuses. Opportunities for professional development include pursuing certifications in tools like AWS.
Responsibilities
- Collaborate with Commercial, Medical, IT teams to identify problems and deliver analytics solutions
- Design, validate, interpret supervised and unsupervised models for decision-making
- Apply causal inference to experimental and observational data for strategy optimization
- Build scalable AI/ML pipelines for high-dimensional datasets
- Leverage US healthcare and pharma knowledge to generate impactful insights
- Translate analytical findings into actionable recommendations for stakeholders
Requirements
- Master’s degree in Statistics, Data Science, Mathematics, Physics, Econometrics, Operations Research, or related quantitative field, or equivalent work experience
- 2+ years of experience as data scientist in commercial setting, pharma preferred
- Strong expertise in supervised and unsupervised learning, causal inference, hypothesis testing, scalable ML pipelines, feature engineering
- Proficiency in Python with pandas and scikit-learn, SQL, Git, Linux, AWS, experience with healthcare datasets like claims data preferred