Data Scientist II

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 . Job Title : Data Scientist II - Commercialization & EF DS & AI Solutions   Profile Summary:   The Data Scientist II role is a high‑impact idea generator and deep problem solver within analytics team. This role is for individuals who can challenge assumptions, conceptualize novel analytical approaches, and harness emerging technologies to deliver transformative business solutions. This role is designed for an experienced data scientist with strong time‑series forecasting expertise who can independently own end‑to‑end forecasting workstreams, improve and scale enterprise forecasting platforms, and lead initiatives that directly influence commercial and strategic decision‑making.  This individual operates with a high degree of autonomy, translating ambiguous business problems into robust forecasting solutions, partnering closely with Finance, Commercial, Market Access, and Analytics stakeholders. The role blends deep technical execution, platform thinking, and stakeholder leadership   Roles & Responsibilities:   Ideate, architect, and prototype high‑impact analytical and ML/AI solutions.   Break down ambiguous business problems into clear, scalable analytical workflows.   Design, develop, and maintain advanced forecasting models using statistical, machine learning, and AI‑driven approaches across commercial demand and planning use cases.  Partner with stakeholders to frame hypotheses, define KPIs, and design experiment frameworks.   Explore and analyse large structured and unstructured datasets from clinical, digital, and real‑world sources.   Apply advanced ML, statistical methods, and LLM‑based techniques to generate business solutions.   Work with engineering teams to ensure reliable data pipelines and deployment environments.   Present complex model logic and recommendations clearly to technical and non‑technical audiences.   Continuously evaluate and adopt emerging AI/ML and agentic‑system tools to future‑proof capabilities.   Mentor junior data scientists and promote a culture of experimentation and innovation.  Apply MLOps best practices including version control, reproducibility, model monitoring, and documentation.

Bachelor’s, Master’s, or Ph.D. in Data Science, Computer Science, Statistics, Engineering, or related field.   2–5 years of experience in applied ML and problem‑solving roles.   Experience working with large structured/unstructured datasets (SQL, NoSQL, document stores).   Demonstrated success building predictive or AI models with measurable business impact.   Experience with healthcare, clinical trials, or regulated pharma datasets (preferred).   Strong hold on MLOps tools: MLflow, Git, CI/CD, containerization.    Skills and Competencies   Strong hands‑on expertise in Python‑based data science and analytical workflows.  Strong foundations in statistics, hypothesis testing, and experimental design.   Excellent communication, storytelling,