Senior Manager Data Scientist

Key Role Overview

This Senior Manager role sits on a new Drug Development Data Science and Biomarker team and focuses on applying advanced computational, statistical, and biological methods to multimodal data (clinical, omics, real-world) to support biomarker strategy and precision medicine. The position is hands-on, requiring development and implementation of machine learning and deep learning approaches, predictive models, and scalable analytical pipelines while partnering closely with translational, clinical, and statistical scientists.

What are the Key Responsibilities?

• Develop and apply novel or existing computational methods for patient segmentation from multimodal clinical and omics datasets in partnership with Translational, Clinical and Statistical Scientists.
• Partner with lead and protocol statisticians to write, review, and execute protocols and statistical analysis plans (SAP) for biomarkers and diagnostics, defining biomarker strategy for clinical drug development.
• Execute biomarker analyses on datasets from BMS clinical trials and real-world data cohorts.
• Perform relevant and innovative statistical analyses of high-dimensional data (e.g., gene expression, sequencing) generated by cutting-edge technologies.
• Execute and contribute to the scientific and statistical strategy of drug development, including development of predictive biomarker(s) and precision medicine approaches.
• Optimize and validate biomarker assays for clinical trial usage.
• Develop, implement, and apply state-of-the-art algorithms to address key business problems and drive implementation of innovative statistical methods in support of biomarker strategy.
• Formulate, implement, test, and validate predictive models and implement efficient automated processes for producing modeling results at scale.
• Collaborate with cross-functional teams including clinicians, data scientists, translational medicine scientists, statisticians, and IT professionals.
• Manage and coordinate resources to produce quality deliverables within timelines for competing priorities.

What are the Required Qualifications?

• Ph.D.: in a relevant quantitative field (Computational Biology, Biostatistics, Statistics, Computer Science, etc.) with 1+ years of academic/industry experience OR Master’s degree in a relevant quantitative field with 3+ years of industry experience.
• Strong experience: in analysis of data generated by one or more -omics or molecular assays (required).
• Strong experience: in biomarker data analysis using data from clinical trials or electronic health records.
• Experience: in modeling methods and their application to pharma R&D.
• Experience: applying AI/ML methods; proficiency in SQL, Python, and R, and experience with cloud platforms.
• Experience: developing statistical and machine learning models on high-dimensional and high-throughput data for time-to-event and longitudinal outcomes.
• Ability: to work independently and collaboratively on multiple concurrent, fast-paced projects; strong problem-solving skills.
• Excellent communication: data presentation, and visualization skills; capable of establishing strong working relationships across the organization.

What are the Preferred Qualifications?

• Knowledge: of molecular biology and understanding of disease pathways.
• Experience: working with real-world data cohorts in addition to clinical trial data.
• Experience: with deep learning approaches and advanced multimodal modeling techniques.
• Experience: optimizing and validating biomarker assays for clinical trial use.
• Demonstrated perspective: in leveraging innovative approaches to expedite drug development and address complexities of emerging data.

Compensation & Benefits

• Princeton, NJ: $164,110 - $198,862 (starting compensation range for this location; final individual compensation will be based on experience).
• Cambridge Crossing: range mentioned in posting: $188,730 - $228,701 (location-specific range referenced in posting).
• Medical, pharmacy, dental, and vision coverage.
• Wellbeing programs (BMS Living Life Better), Employee Assistance Programs (EAP), and other wellbeing supports.
• Financial well-being resources including a 401(k) plan and financial protection benefits (short- and long-term disability, life insurance, supplemental health insurance).
• Paid time off programs, paid national holidays, Global Shutdown Days, volunteer days, and other leave programs (parental, caregiver, bereavement, military) per eligibility.
• Additional perks such as tuition reimbursement and employee recognition programs; eligibility for incentive cash and stock opportunities may apply.

Additional Information

• Work arrangement: role location listed as Princeton, NJ. BMS uses an occupancy protocol (site-essential, site-by-design, field-based, remote-by-design) to determine onsite requirements; some roles may be eligible for hybrid work with at least 50% onsite presence.
• Applicants: requiring reasonable workplace accommodations/adjustments can contact adastaffingsupport@bms.com.
• BMS will consider qualified applicants with arrest and conviction records and provides data protection guidance; the company will not request payments or sensitive personal financial information during recruitment.
• Requisition number: R1598755.