Senior Manager, Data Science

Bristol Myers Squibb · Hyderabad

Collected role 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. <h2></h2><h2>Position Summary</h2>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.<h3>What You’ll Do (Hands-on Responsibilities)</h3><ul><li>Build and maintain Python pipelines for wearable time-series data, including:<ul><li>QC, preprocessing, and sensor artifact removal</li><li>Imputation (baseline through advanced methods) and feature engineering based on clinical concepts of interest</li><li>EDA and signal characterization for accelerometry/actigraphy, HRV, and SpO₂</li><li>Signal processing and signal detection</li></ul></li><li>Develop and validate models for longitudinal sensor data using:<ul><li>Frequency / time-frequency representations, digital filtering, and representation learning</li><li>Quantitative characterization of physiological and clinically meaningful measures provably associated with disease progression or subtyping. </li><li>Deep learning approaches (Transformers and/or ensembles) with model explainability techniques where appropriate</li></ul></li><li>Apply statistically rigorous approaches to repeated-measures data:<ul><li>Longitudinal statistical modeling (e.g., mixed effects / hierarchical models)</li><li>Study-appropriate strategies for within-subject dynamics and missingness</li></ul></li><li>Implement strong evaluation practices and reproducible research standards:<ul><li>Nested CV, LOO, and/or OOB methods where appropriate</li><li>Reproducible experimentation, documentation, and well-structured codebases</li></ul></li><li>Collaborate actively with internal stakeholders (clinical, stats, engineering, product) and external partners / third-party analytics providers, including QC and validation of vendor-derived outputs.</li><li>Contribute to team excellence via code reviews, technical mentorship (scope depends on level), and raising engineering rigor.</li></ul><h3>Required Qualifications</h3><ul><li>PhD (preferred) or MS with strong experience in Data Science, Biostatistics, Biomedical Engineering, Computer Science, or related field.</li><li>PhD 3-5 years, MS 6-9 years, prior experience working on digital health initiatives within pharma industry, medical devices etc.. </li><li>Demonstrated hands-on experience with time-series sensor data, including:<ul><li>QC, preprocessing, artifact handling, imputation, feature engineering for accelerometry/actigraphy</li><li>Experience with HRV and/or SpO₂</li></ul></li><li>Strong Python skills with evidence of shipping code:<ul><li>Clean, testable code; object-oriented design; modular pipelines</li><li>Git/version control, code reviews, and collaborative development practices</li></ul></li><li>Experience with longitudinal statistical modeling for repeated measures data.</li><li>Proven ability to translate analytical work into clear deliverables and communicate results to technical and non-technical stakeholders.</li></ul><h3>Preferred Qualifications (one or more of the following)</h3><ul><li>“Navigational physics” experience for movement data and/or biomechanical analysis (a plus): quaternions, Euler angles, dead-reckoning, orientation/heading estimation, etc.</li><li>Familiarity with sleep analytics and/or circadian cosinor modeling (or willingness to learn open-source libraries).</li><li>Experience managing or integrating third-party analytics (e.g., actigraphy QC workflows) and validating vendor outputs.</li><li>Experience with scalable compute and deployment patterns, including:<ul><li>AWS experience; multi-GPU instances and parallelization for model training/inference</li></ul></li></ul><h3>Why Join Us</h3><ul><li>Work at the intersection of digital biomarkers, machine learning, and clinical development</li><li>Partner with multidisciplinary teams to advance analytics from real-world and trial-based wearable signals</li><li>Build practical, validated solutions with high impact—and write the code that delivers them</li></ul> 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 WorkWhere 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 <a target="_blank" href="https://careers.bms.com/life-at-bms/ways-of-working/">https://careers.bms.com/ways-of-working.</a> Supporting People with DisabilitiesBMS 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 <a target="_blank" href="mailto:adastaffingsupport@bms.com">adastaffingsupport@bms.com</a>. Visit <a target="_blank" href="https://careers.bms.com/eeo-accessibility">careers.bms.com/eeo-accessibility</a> to access our complete Equal Employment Opportunity statement. Candidate RightsBMS 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: <a target="_blank" href="https://careers.bms.com/california-residents/">https://careers.bms.com/california-residents/</a> Data ProtectionWe will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at <a target="_blank" href="http://careers.bms.com/fraud-protection">https://careers.bms.com/fraud-protection</a>. 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 <a target="_blank" href="mailto:TAEnablement@bms.com">TAEnablement@bms.com</a> 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. R1601747 : Senior Manager, Data Science

Collected experience requirement

3-5 years