Associate Director, Data Science

Bristol-Myers Squibb; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Bristol Myers Squibb seeks a senior data science leader to drive strategy and execution across global drug development programs. You will oversee complex analytics on multimodal clinical and omics data, applying rigorous statistical methods and AI/ML techniques to inform decision-making.

This role emphasizes collaboration with Biostatistics, Translational and Clinical Scientists, and cross-functional teams, with potential small-team management and a focus on reproducible pipelines and scalable

Qualifications

• Seasoned data scientist with a strong computational, statistical, and biological background.
• Proven track record of leading analytical strategy and translating complex data into insights.
• Experience leading data science efforts across early-to-late phase drug development programs.
• Ability to lead a small team of data scientists.

Responsibilities

• Provide strategic direction and methodological guidance on data science approaches across drug development programs.
• Lead design and execution of exploratory and confirmatory analyses across diverse data types.
• Drive development and implementation of innovative statistical methods and AI/ML approaches.
• Shape analytical strategy for trial design, endpoint selection, biomarker strategy, and evidence generation.
• Represent DSAA in cross-functional program team meetings and influence development decisions through data-driven analysis.
• Lead development of patient segmentation and biomarker discovery with multimodal datasets in partnership with Translational, Clinical, and Statistical Scientists.

Skills

Computational statistics

Biomarker analytics

Data science leadership

AI/ML applications

Clinical data integration

Tools

Python

R

SQL

Cloud platforms (AWS/GCP)

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

This is a new position. You will join a cutting-edge Drug Development Data Science and Advanced Analytics (DSAA) team as a senior scientific and technical leader, driving data science strategy and execution to advance the global drug development process. We are looking for a seasoned data scientist with a strong computational, statistical, and biological background and a demonstrated track record of leading analytical strategy, driving methodological innovation, and translating complex, multi-modal data into impactful scientific insights that inform clinical development decisions.

As an Associate Director, you will provide scientific leadership across diverse data types generated in drug development - including clinical trial data, genomics, proteomics, imaging, flow cytometry, and other biomarker modalities - driving both the strategic direction and hands-on execution of data science efforts across early-to-late phase drug development programs. You will define and champion analytical frameworks, methodological standards, and scalable approaches that elevate the quality and impact of data science across the organization, while serving as a key scientific partner to Biostatistics leads, Translational and Clinical Scientists, and senior cross-functional stakeholders. This position may include management of a small team of data scientists. We are looking for a technically excellent, scientifically influential, and strategically minded practitioner.

What You'll Do

Data Science Strategy & Scientific Leadership

• Serve as a senior scientific resource within the DSAA organization, providing strategic direction and methodological guidance on data science approaches across multiple drug development programs
• Lead the design and execution of exploratory and confirmatory analyses (both hypothesis-generating and hypothesis-driven) across diverse and complex data types, from early discovery through late-phase clinical development
• Drive the development and implementation of innovative statistical methods, novel analytical frameworks, and state-of-the-art AI/ML approaches to address key scientific questions in drug development
• Shape the analytical strategy for drug development programs, contributing to decisions around trial design, endpoint selection, biomarker strategy, and evidence generation
• Identify opportunities to leverage emerging data science methodologies and technologies to accelerate drug development and address the complexities of novel data types
• Represent DSAA in cross-functional program team meetings, providing authoritative scientific input and influencing development decisions through rigorous, data-driven analysis

Advanced Analytics & Modeling

• Lead the development and application of novel computational methods for patient segmentation, biomarker discovery, and precision medicine from multimodal clinical and omics datasets in partnership with Translational, Clinical, and Statistical Scientists
• Oversee and execute data science analyses on datasets from BMS clinical trials and real-world data cohorts, spanning genomics, proteomics, imaging, flow cytometry, and other high-dimensional biomarker data types
• Drive the integration, mining, and visualization of diverse, high-dimensional, and disparate datasets across therapeutic areas and development phases, developing novel analytical approaches where existing methods fall short
• Lead the formulation, implementation, testing, and validation of predictive models and scalable automated processes for delivering modeling results across multiple programs
• Apply and advance the use of AI/ML, deep learning, NLP, causal ML, and explainable AI across multiple data modalities and clinical development contexts, maintaining currency with the state of the art
• Lead application of rigorous statistical approaches to clinical trial data, including survival analysis, longitudinal/mixed-effects modeling, causal inference, and principled handling of missing data and censoring
• Contribute to and influence the scientific and statistical strategy of drug development programs, including the development of predictive biomarkers, novel trial designs, and precision medicine approaches

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 assess and e