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About the Role
Bristol Myers Squibb is seeking an Associate Director of Data Science to join the Drug Development Data Science & Advanced Analytics (DSAA) team. This role operates at the intersection of advanced analytics, AI/ML innovation, and clinical science, driving strategic direction and hands-on execution across drug development programs. The position offers a unique opportunity to define analytical frameworks, champion methodological standards, and partner with cross-functional stakeholders.
Responsibilities
- 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.
- 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.
- Lead the development and application of novel computational methods for patient segmentation, biomarker discovery, and precision medicine.
- Drive the integration, mining, and visualization of diverse, high-dimensional datasets across therapeutic areas and development phases.
- 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.
- Define and champion standards for scalable, reproducible, and well-documented analytical pipelines and codebases.
- Establish and enforce data quality frameworks to ensure fitness-for-purpose of diverse data sources.
- Drive adoption of scalable, automated analytical processes and best-in-class software engineering practices.
- 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.
- 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.
Requirements
- 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 outcomes.
- Proven expertise in AI/ML and proficiency in Python, R, SQL, and cloud platforms (e.g., AWS, Azure, Databricks).
- Deep familiarity with clinical trial design, drug development processes, and the role of biomarkers and data science in regulatory and clinical decision-making.
- Demonstrated ability to define and drive analytical strategy across multiple concurrent programs, balancing scientific rigor with practical delivery.
- Excellent communication, data presentation, and visualization skills with the ability to convey complex concepts to diverse audiences.
- Experience with genomics, proteomics, imaging, flow cytometry, or immunobiology datasets from clinical trials.
- Experience with NLP, causal ML, explainable AI, and survival analysis/time-to-event modelling.
- Knowledge of molecular biology and understanding of disease pathways.
- Experience with real-world data (RWD/RWE) sources, including EHR, claims, or registry data.
- Familiarity with novel clinical trial designs (e.g., adaptive, platform, or biomarker-enriched trials).
- Prior experience in a people management or formal scientific leadership role.
- Experience with cloud-based scalable compute and deployment patterns for large-scale data processing and model training.
Skills
- Data Science
- Statistical Analysis
- Machine Learning
- AI/ML
- Python
- R
- SQL
- Cloud Platforms (AWS, Azure, Databricks)
- Data Visualization
- NLP
- Causal ML
- Explainable AI
- Survival Analysis
- Time-to-Event Modelling
- Genomics
- Proteomics
- Imaging
- Flow Cytometry
- Immunobiology
- Real-World Data (RWD/RWE)
- EHR
- Claims Data
- Registry Data
- Novel Clinical Trial Designs
Location
- Remote-by-design
Work Type
- Hybrid
Experience Level
- Associate Director
- 6+ years academic/industry experience (PhD)
- 8+ years industry experience (Master's)
Education Level
- PhD in a relevant quantitative field
- Master's Degree in a relevant quantitative field
Benefits
- Opportunities for growth
- Supportive environment
- Inclusion
- Wellbeing
- Flexibility
- Comprehensive benefits
About the Company
- Bristol Myers Squibb's 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.
Equal Opportunity
- 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.
- Bristol Myers Squibb is Disability Confident – Employer
- BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.