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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager, Data Sciences - **Company:** Bristol-Myers Squibb Company - **Location:** Uxbridge, UK - **Experience:** Expert - **Salary:** £72,511.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Code Review, Computational Biology, Information Engineering, Data Governance, Data Presentation, EHealth, R (Programming Language), Python (Programming Language), Machine Learning, SQL Databases, Explainable AI (XAI), Deep Learning, Model Validation, Electronic Medical Records, Information Technology, Databricks - **Published:** October 15, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5928723213 ## About the Role * PhD in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, or Computer Science) with 1+ years of academic/industry experience; or a Master's Degree in a relevant quantitative field with 3+ years of industry experience * Strong experience in data science and statistical analysis using clinical trial or electronic health records data, particularly in a pharma R&D context * Experience developing and validating statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes * Experience in the application of AI/ML and proficiency in Python, R, SQL, and cloud platforms (e.g., AWS, Azure, Databricks) * Familiarity with clinical trial design, drug development processes, and the role of biomarkers in regulatory and clinical decision-making * A perspective on leveraging innovative approaches to expedite drug development and address the complexities of emerging data types * Strong problem-solving, collaboration, and communication skills, with the ability to handle several concurrent, fast-paced projects independently and as part of a team, * 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 and associated analytical methods * Familiarity with digital health data and wearable/sensor-derived data types * Experience with cloud-based scalable compute and deployment patterns for large-scale data processing and model training ## Description * 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 * Develop innovative approaches to integrating, mining, and visualising diverse, high-dimensional, and disparate datasets generated across early-to-late phase drug development * Formulate, implement, test, and validate predictive models and build efficient, automated processes for delivering modelling results at scale * Apply modern machine learning capabilities - including AI/ML, deep learning, NLP, causal ML, and explainable AI - across multiple data modalities and clinical development contexts * Apply statistically rigorous approaches to clinical trial data, including survival analysis, longitudinal/mixed-effects modelling, and appropriate handling of missing data and censoring * Contribute to 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 * Build and maintain well-structured, reproducible, version-controlled analytical pipelines and codebases using Python, R, SQL, and cloud platforms * Develop and apply data quality frameworks to assess and ensure fitness-for-purpose of diverse data sources for specific analytical questions * Implement strong model evaluation practices including cross-validation strategies, calibration assessment, and transparent reporting of model performance and limitations * Build scalable, automated processes for delivering analytical results across multiple programs and data types Collaboration & Technical Contribution * Partner with lead and protocol statisticians in contributing to statistical analysis plans (SAPs) for exploratory data science analyses supporting drug development programs * Collaborate with cross-functional teams including clinicians, translational medicine scientists, biostatisticians, data engineers, and IT/engineering professionals * Contribute to team excellence through code reviews, technical mentorship, and raising the overall engineering and methodological standards of the team * Communicate analytical strategies and results clearly and effectively to both technical and non-technical stakeholders, with strong data presentation and visualisation skills * Manage and coordinate deliverables across concurrent, fast-paced projects within tight timelines, 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.