Senior Data Scientist

Bristol-Myers Squibb Co; Hyderabad; On-site; INR 1,600,000 - 2,600,000; Full time

Job summary

Bristol Myers Squibb is seeking a Senior Data Scientist III to design and implement advanced ML/AI solutions within Clinical Development analytics. You will work closely with clinical, medical, and operational teams to translate complex data into actionable insights, while delivering robust data pipelines and modeling workflows.

The role emphasizes hands-on technical delivery, statistical rigor, and independent problem solving in a collaborative environment driven by patient impact.

Qualifications

• Bachelor's or higher in Data Science, Statistics, Biostatistics, Computer Science, or related field.
• 5+ years of progressive experience in data science or ML engineering in biopharma/pharma/clinical research.
• Experience with clinical trial data, EHR/EMR, or RWE/RWD sources; data governance in regulated environments.

Responsibilities

• Design and build ML/AI solutions for clinical development analytics.
• Conduct rigorous statistical analyses on clinical datasets and translate findings into actionable insights.
• Develop data pipelines and collaborate with engineers on scalability and reliability.

Skills

Python

PySpark

R

Statistical analyses

Machine learning

AI/GenAI

LLMs

Education

Bachelor's or higher in Data Science/Statistics/CS

MS/PhD desirable

Tools

Airflow

Kedro

Dagster

Spark

GitHub

AWS/Azure

Job description

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Position Summary

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.

Stakeholder Engagement & Communication Collaborate with clinical, medical, and scientific stakeholders to define project objectives, shape data‑driven hypotheses, and align on KPIs. Present analytical findings and recommendations to functional leads and cross‑functional teams through clear visualizations and structured narratives. Communicate trade‑offs between analytical approaches clearly and confidently, with appropriate scientific justification.

Engineering & MLOps Practices Apply MLOps and GitOps practices in your own work — ensuring models and pipelines are versioned,documented, and maintainable. Adhere to and actively contribute to engineering standards, code quality, and best practices established by the team. Work within cloud platforms (AWS/Azure), big data technologies (Spark), and version control tooling(GitHub) at scale. Support junior data scientists with technical guidance and peer code review as needed.

Skills & Competencies

Technical Skills

• Strong proficiency in Python, PySpark, or R — including clinical and statistical packages and ML frameworks.
• Solid understanding of experimental design, hypothesis testing, survival analysis, and clinical trial statistical methodologies.
• Hands‑on experience with modern data pipeline and orchestration frameworks (e.g., Kedro, Dagster,Airflow).
• Practical working knowledge of AI/GenAI technologies — LLMs, RAG frameworks, Agentic AI, and prompt engineering.
• Experience with agentic AI frameworks such as LangChain, AutoGen, LlamaIndex, or OpenAI Agents in project or near-production settings.
• Familiarity with SDLC principles; exposure to front‑end development (e.g., React) is a plus.
• Understanding of clinical trial data structures and standards.
• Familiarity with real‑world data (RWD) sources including claims, EHR/EMR, an patient registries.

Soft Skills

• Clear and structured communication — able to present complex findings to both technical peers and clinical stakeholders.
• Strong analytical and problem‑solving skills with the ability to navigate ambiguity independently.
• Collaborative mindset with a drive for scientific rigor and continuous learning.
• Ability to evaluate and articulate trade‑offs between different methodologies with sound judgment.

Experience

• Experience Bachelor's, Master's, or Ph.D. in Data Science, Statistics, Biostatistics, Computer Science, or a related discipline.
• 5+ years of progressive experience in data science or ML engineering, with meaningful exposure to biopharma, pharma, or clinical research settings.
• Demonstrated track record of delivering end‑to‑end analytical or ML solutions — from problem framing through deployment.
• Experience working with clinical trial data, EHR/EMR, or RWE/RWD sources; Understanding of data governance in regulated environments.
• Working knowledge of the biopharma drug development lifecycle — clinical phases, regulatory landscape, and data standards.
• Practical experience with AI/GenAI technologies — LLMs, RAG, Agentic AI, and prompt engineering —applied to real or near‑real use cases.
• Familiarity with model explainability (XAI) and HIPAA compliance considerations in clinical data workflows.
• Experience contributing to capability assessments or tool evaluations is a plus.

Good to Have

• Hands‑on experience with LLM‑driven or LLM‑augmented workflows in a clinical or drug development context.
• Experience building and deploying data science applications with a React‑based front end and Python/API‑driven back end.
• Familiarity with responsible AI principles — fairness, transparency, and explainability in clinical settings.
• Contributions to open‑source AI/GenAI projects, publications, or participation in relevant hackathons or conferences.
• Exposure to AI/ML capability roadmap initiatives or center-of-excellence (CoE) contributions.

How We Work

Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote‑by‑design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways‑of‑working.

Supporting People with Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to [e-mail]. Visit careers.bms.com/eeo‑accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california‑residents/

Data Protection

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We’re creating innovative medicines for patients fighting serious diseases. We’re also nurturing our own diverse team with inspiring work and challenging career options. No matter the role, each one of us makes a contribution. And that makes all the difference.