Data Scientist III - Bristol-Myers Squibb

Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us .

Role Overview

As a Data Scientist III, you will be a strong individual contributor embedded in the Clinical Development analytics function. You will design and build sophisticated ML and AI solutions, conduct rigorous statistical analyses on clinical datasets, and collaborate closely with clinical, medical, and operational stakeholders to translate complex data into actionable insights. This role emphasizes hands-on technical delivery, sound scientific judgment, and the ability to work independently on moderately complex to complex problems.

Roles & Responsibilities

Analytical Delivery & Modeling

• Design, develop, and deploy predictive modeling and data science solutions — including regression, clustering, survival analysis, time series forecasting, and Monte Carlo simulation — to address clinical development challenges.
• Conduct rigorous statistical investigations and exploratory data analysis across clinical datasets including trial data, EHR/EMR, and real-world evidence (RWE).
• Translate moderately ambiguous scientific or operational problems into structured, hypothesis-driven analytical frameworks spanning study feasibility, trial execution, and patient analytics.
• Build and maintain data and analytics pipelines — contributing to pipeline design decisions and ensuring computational efficiency within established architectural patterns.
• Partner with senior data scientists and engineering teams on data quality, pipeline reliability, and scalability improvements.

AI & GenAI Solutions

• Design and implement AI/GenAI-powered solutions — including LLMs, RAG frameworks, and Agentic AI architectures — to augment clinical workflows and decision-making under senior guidance.
• Apply prompt engineering best practices and contribute to LLM orchestration patterns within the clinical development context.
• Stay current with emerging AI/ML methodologies and proactively surface opportunities to apply new techniques to clinical problems.