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Original posting from 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.
Shape the Future of Drug Development
Are you a data science leader with the vision to transform complex, multi-modal data into life-changing scientific decisions? Bristol Myers Squibb is looking for an Associate Director of Data Science to join our cutting-edge Drug Development Data Science & Advanced Analytics (DSAA) team.
This is a rare opportunity to operate at the intersection of advanced analytics, AI/ML innovation, and clinical science — driving both strategic direction and hands-on execution across early-to-late phase drug development programs. As a senior scientific and technical leader, you will define analytical frameworks, champion methodological standards, and serve as a key partner to cross-functional stakeholders across the organization.
What You'll Do
Data Science Strategy & Scientific Leadership
- Serve as a senior scientific resource within DSAA, providing strategic direction and methodological guidance across multiple drug development programs
- Lead the design and execution of exploratory and confirmatory analyses across diverse and complex data types — from early discovery through late-phase clinical development
- Shape analytical strategy for drug development programs, contributing to decisions around trial design, endpoint selection, biomarker strategy, and evidence generation
- Represent DSAA in cross-functional program team meetings, providing authoritative scientific input and influencing development decisions through rigorous, data-driven analysis
Advanced Analytics & Modelling
- Lead the development and application of novel computational methods for patient segmentation, biomarker discovery, and precision medicine from multimodal clinical and omics datasets
- Drive the integration, mining, and visualization of diverse, high-dimensional datasets across therapeutic areas and development phases — including genomics, proteomics, imaging, and flow cytometry
- Apply and advance the use of AI/ML, deep learning, NLP, causal ML, and explainable AI across multiple data modalities and clinical development contexts
- Lead application of rigorous statistical approaches to clinical trial data, including survival analysis, longitudinal/mixed-effects modelling, causal inference, and principled handling of missing data
Data Engineering & Reproducibility
- Define and champion standards for scalable, reproducible, and well-documented analytical pipelines and codebases using Python, R, SQL, and cloud platforms
- Establish and enforce data quality frameworks to ensure fitness-for-purpose of diverse data sources across programs
- Drive adoption of scalable, automated analytical processes and best-in-class software engineering practices across the team
Leadership, Mentorship & Cross-Functional Influence
- Manage and develop a small team of data scientists, building capabilities and fostering scientific rigor and innovation
- Mentor junior and mid-level data scientists, elevating team-wide methodological and engineering standards through code reviews, collaborative problem-solving, and knowledge sharing
- Partner with lead and protocol statisticians in shaping statistical analysis plans (SAPs) for exploratory data science analyses
- Communicate complex analytical strategies and results with clarity and scientific authority to both technical and non-technical audiences, including senior leadership
What We're Looking For
Required Qualifications:
- PhD in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, or Computer Science) with 6+ years of academic/industry experience; or a Master's Degree in a relevant quantitative field with 8+ years of industry experience
- Demonstrated mastery in data science and statistical analysis using clinical trial or electronic health records data, with a strong track record of delivering impactful results in a pharma R&D context
- Significant experience leading the development and application of statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate o
Source: Bristol-Myers Squibb careers