Senior Manager, Data Science

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

BMS Digital Health is seeking a Senior Manager, Data Science to build and deliver hands-on, code-first analytics and algorithm development using wearable and sensor-derived longitudinal data . This role is for a data scientist who thrives in the details—owning work end-to-end from raw signals to validated outputs—spanning time-series QC, preprocessing, artifact handling, imputation, feature engineering, and modeling across accelerometry/actigraphy and cardio-respiratory signals (e.g., HRV, SpO₂). The ideal candidate enjoys writing production-quality Python in orchestration environments, applying rigorous validation, and collaborating across internal and external partners.

This is a highly hands-on individual contributor role. You will spend a significant portion of your time coding, debugging, reviewing PRs, and building reproducible pipelines and models.

• Build and maintain Python pipelines for wearable time-series data, including:

  • QC, preprocessing, and sensor artifact removal

  • Imputation (baseline through advanced methods) and feature engineering based on clinical concepts of interest

  • EDA and signal characterization for accelerometry/actigraphy, HRV, and SpO₂

  • Signal processing and signal detection

• Develop and validate models for longitudinal sensor data using:

  • Frequency / time-frequency representations, digital filtering, and representation learning

  • Quantitative characterization of physiological and clinically meaningful measures provably associated with disease progression or subtyping. 

  • Deep learning approaches (Transformers and/or ensembles) with model explainability techniques where appropriate

• Apply statistically rigorous approaches to repeated-measures data:

  • Longitudinal statistical modeling (e.g., mixed effects / hierarchical models)

  • Study-appropriate strategies for within-subject dynamics and missingness

• Implement strong evaluation practices and reproducible research standards:

  • Nested CV, LOO, and/or OOB methods where appropriate

  • Reproducible experimentation, documentation, and well-structured codebases

• Collaborate actively with internal stakeholders (clinical, stats, engineering, product) and external partners / third-party analytics providers, including QC and validation of vendor-derived outputs.

• Contribute to team excellence via code reviews, technical mentorship (scope depends on level), and raising engineering rigor.

• PhD (preferred) or MS with strong experience in Data Science, Biostatistics, Biomedical Engineering, Computer Science, or related field.

• PhD 3-5 years, MS 6-9 years, prior experience working on digital health initiatives within pharma industry, medical devices etc..

• Demonstrated hands-on experience with time-series sensor data, including:

  • QC, preprocessing, artifact handling, imputation, feature engineering for accelerometry/actigraphy

  • Experience with HRV and/or SpO₂

• Strong Python skills with evidence of shipping code:

  • Clean, testable code; object-oriented design; modular pipelines

  • Git/version control, code reviews, and collaborative development practices

• Experience with longitudinal statistical modeling for repeated measures data.

• Proven ability to translate analytical work into clear deliverables and communicate results to technical and non-technical stakeholders.

• “Navigational physics” experience for movement data and/or biomechanical analysis (a plus): quaternions, Euler angles, dead-reckoning, orientation/heading estimation, etc.

• Familiarity with sleep analytics and/or circadian cosinor modeling (or willingness to learn open-source libraries).

• Experience managing or integrating third-party analytics (e.g., actigraphy QC workflows) and validating vendor outputs.

• Experience with scalable compute and deployment patterns, including:

  • AWS experience; multi-GPU instances and parallelization for model training/inference

• Work at the intersection of digital biomarkers, machine learning, and clinical development

• Partner with multidisciplinary teams to advance analytics from real-world and trial-based wearable signals

• Build practical, validated solutions with high impact—and write the code that delivers them

If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Uniquely Interesting Work, Life-changing Careers
With a single vision as inspiring as “Transforming patients’ lives through science™ ”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

On-site Protocol

BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:

Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.

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 [email protected]. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

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

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