Associate Director, Data Science
Uxbridge - GB
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingSet analytical strategy for trial design, endpoints and biomarkers
Develop AI/ML methods for patient segmentation and biomarker discovery
Lead statistical analysis of clinical trial data, including survival and longitudinal models
Set standards for reproducible analytical pipelines and data quality
Manage and mentor a small team of data scientists
From the employer’s posting
Shape analytical strategy for drug development programs, contributing to decisions around trial design, endpoint selection, biomarker strategy, and evidence generation
Lead the development and application of novel computational methods for patient segmentation, biomarker discovery, and precision medicine from multimodal clinical and omics datasets
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
Define and champion standards for scalable, reproducible, and well-documented analytical pipelines and codebases using Python, R, SQL, and cloud platforms
Manage and develop a small team of data scientists, building capabilities and fostering scientific rigor and innovation
What you’ll bring
All qualificationsCore experience
- 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
Preferred experience
- 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
Qualification wording
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
Education & alternatives
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
Tools in this posting
- Python
- R
- SQL
- AWS
- Azure
- Databricks
Source — Tool mentions in context
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
- 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
Posting record
Report an errorOpen 6 monthsWe first saw this posting 184 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 27, 2026 · 184 days ago
- Recorded sightings
- 160
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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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.
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 DoData 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
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 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
Preferred Qualifications:
- 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
#LI-Hybrid
We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.
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 adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Bristol Myers Squibb is Disability Confident – Employer
A UK Government scheme
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
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection.
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.com with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.
R1600843 : Associate Director, Data Science
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Uxbridge - GB
- Experience with cloud-based scalable compute and deployment patterns for large-scale data processing and model training #LI-Hybrid We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.
More source context
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
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