Senior Data Science Manager – Drug Development

Bristol-Myers Squibb Co; Uxbridge; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Comprehensive benefits

Flexible work model

Wellbeing support

Job summary

Bristol Myers Squibb is seeking a Senior Manager, Data Sciences to join the Drug Development Data Science & Advanced Analytics (DSAA) team. You will lead exploratory and confirmatory analyses across clinical trials, genomics, proteomics, imaging, and other omics data to support decisions across the development pipeline.

This role emphasizes interface between computational science and drug development, with responsibility for scalable data pipelines, model validation, and cross-functional

Qualifications

• PhD in a relevant quantitative field with 1+ years of academic/industry experience or a Master’s with 3+ years industry experience.
• Strong data science and statistical analysis experience in pharma/R&D context.
• Experience with AI/ML, NLP, causal ML, and survival/time-to-event modelling.

Responsibilities

• Develop and apply novel computational methods for patient segmentation and biomarker discovery across multimodal data.
• Execute data science analyses on clinical trial and real-world data cohorts.
• Build predictive models and scalable automated processes for results delivery.
• Apply ML across multiple data modalities and development contexts.
• Contribute to statistical analysis plans and collaborate with cross-functional teams.
• Communicate strategies and results clearly to technical and non-technical stakeholders.

Skills

PhD/Quant degree

Python

R

SQL

Education

PhD in quantitative field

MS in quantitative field

Tools

AWS/Azure/Databricks

Job description

Bristol Myers Squibb is seeking a Senior Manager, Data Sciences to join the Drug Development Data Science & Advanced Analytics (DSAA) team. You will lead exploratory and confirmatory analyses across clinical trials, genomics, proteomics, imaging, and other omics data to support decisions across the development pipeline.

This role emphasizes interface between computational science and drug development, with responsibility for scalable data pipelines, model validation, and cross-functional