Director

Bristol Myers Squibb • Princeton, NJ

1d

About The Position

Working at Bristol Myers Squibb offers challenging, meaningful, and life-changing work, transforming patients' lives through science. Employees have opportunities to grow and thrive alongside high-achieving teams. Bristol Myers Squibb values balance and flexibility, offering competitive benefits, services, and programs. This new Director position is within a cutting-edge Drug Development Data Science and Advanced Analytics (DSAA) team, aiming to drive and shape the global drug development process. The role seeks a seasoned, scientifically accomplished data scientist with a proven track record in leading analytical strategy, translating complex multi-modal data into scientific insights, and influencing drug development decisions. It requires deep expertise in digital health data science, including wearable and sensor-derived longitudinal data, along with strategic and hands-on contributions across genomics, proteomics, imaging, flow cytometry, and other biomarker data types from clinical trials. As a Director, the individual will be a recognized scientific and technical leader within DSAA, driving the vision, methodology, and execution of exploratory data science efforts across early-to-late phase drug development. They will define and champion approaches, frameworks, algorithms, and platforms for analytics, visualization, and decision support for drug development scientists and project teams. The position may involve managing a small team of data scientists and requires close collaboration with Biostatistics leads, Translational and Clinical Scientists, and other senior cross-functional partners to integrate data science work into BMS product development, regulatory, and commercial strategies.

Requirements

• Ph.D. in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, Computer Science, or related field) and 8+ years of academic/industry experience; or Master's Degree in a relevant quantitative field and 10+ years of industry experience
• Deep, hands-on expertise in digital health data science, including wearable/sensor time-series data (QC, preprocessing, artifact handling, imputation, feature engineering for accelerometry/actigraphy, HRV, SpO₂), with a track record of delivering validated, production-quality outputs
• Demonstrated mastery in data analysis with data generated from clinical trials or electronic health records, particularly in application to pharma R&D
• Significant industry track record of driving statistical and AI/ML innovation across multiple data modalities and drug development contexts
• Strong Python skills and experience leading code-first, production-quality analytical work: clean, scalable, modular pipelines; Git/version control; and collaborative software development practices
• Mastery in developing and applying statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes
• Deep familiarity with clinical trial design, drug development processes, and the role of biomarkers in regulatory and clinical decision-making
• Proven ability to influence scientific strategy and drive decisions through rigorous, data-driven analysis
• Demonstrated ability to lead, mentor, and collaborate with multidisciplinary teams, and to manage multiple concurrent high-priority programs
• Excellent communication, data presentation, and visualization skills; ability to convey complex analytical concepts to diverse audiences including senior leadership
• Capable of establishing and sustaining strong, high-trust working relationships across the organization

Nice To Haves

• Experience with genomics, proteomics, imaging, flow cytometry, or immunobiology datasets from clinical trials
• Experience with NLP
• Experience with Survival Analysis and time-to-event modeling
• Experience with causal ML and explainable AI
• Knowledge of molecular biology and understanding of disease pathways
• Experience with or perspective on novel trial design (e.g., adaptive, platform, or biomarker-enriched trials)
• Familiarity with sleep analytics, circadian cosinor modeling, or biomechanical/navigational physics for movement data (quaternions, Euler angles, orientation estimation)
• Experience overseeing or integrating third-party analytics partnerships and critically evaluating vendor-derived outputs
• Experience with scalable compute and deployment patterns, including cloud platforms (e.g., AWS), multi-GPU instances, and parallelization for model training/inference at scale
• Prior experience in a people management or formal scientific leadership role is a plus

Responsibilities

• Lead the strategy and hands-on execution of data science efforts for wearable and sensor-derived time-series data, including the design and oversight of Python pipelines for QC, preprocessing, sensor artifact removal, imputation, and feature engineering based on clinical concepts of interest
• Drive development and validation of advanced models for longitudinal sensor data, spanning frequency/time-frequency representations, digital filtering, representation learning, and deep learning approaches (e.g., Transformers, ensembles) with rigorous model explainability
• Define and implement statistically rigorous approaches to repeated-measures and longitudinal data, including mixed-effects/hierarchical models and principled strategies for within-subject dynamics and missingness
• Lead quantitative characterization of physiological and clinically meaningful measures (e.g., accelerometry/actigraphy, HRV, SpO₂) associated with disease progression, patient subtyping, or treatment response, with an eye toward regulatory-grade evidence generation
• Oversee and critically evaluate third-party analytics providers and vendor-derived digital biomarker outputs, ensuring scientific validity and fit-for-purpose quality
• Champion strong evaluation standards, reproducible research practices, and scalable engineering principles across digital health workstreams
• Drive the scientific strategy and execution of data science and biomarker analyses across multimodal clinical, digital health, and omics datasets, including genomics, proteomics, imaging, flow cytometry, and other high-dimensional biomarker data types from BMS clinical trials and real-world cohorts
• Lead and shape the development and application of novel computational methods for patient segmentation, predictive biomarker discovery, and precision medicine in partnership with Translational, Clinical, and Statistical Scientists
• Provide senior scientific input into statistical analysis plans (SAPs) for exploratory biomarker and digital health analyses, shaping the data science strategy for clinical drug development programs
• Perform and oversee innovative statistical analyses of high-dimensional data (e.g., gene expression, sequencing, imaging features) generated by cutting-edge technologies, ensuring methodological rigor and interpretability
• Lead the integration, mining, and visualization of diverse, high-dimensional, and disparate datasets across therapeutic areas and development phases, developing novel analytical frameworks where existing approaches fall short
• Drive the formulation, implementation, testing, and validation of predictive models and scalable automated processes for delivering modeling results across programs
• Champion the application of modern machine learning capabilities, including AI/ML, deep learning, NLP, causal ML, and explainable AI, to accelerate drug development and address the complexities of emerging data types
• Contribute to and influence the scientific and statistical strategy of drug development programs, including the development of predictive biomarkers, novel trial designs, and precision medicine approaches
• Serve as a senior scientific thought leader within the DSAA organization, shaping the vision and roadmap for digital health and multi-modal data science in drug development
• If applicable, manage and develop a small team of data scientists, building capabilities, fostering a culture of rigor and innovation, and ensuring delivery of high-quality work
• Build and sustain strong partnerships with senior stakeholders across Biostatistics, Translational Medicine, Clinical Development, Regulatory Affairs, and IT/Engineering
• Lead cross-functional scientific discussions, represent DSAA in project team meetings, and influence drug development decisions through data-driven insights
• Establish and promote best practices, methodological standards, and engineering quality across DSAA, mentoring junior and mid-level data scientists
• Communicate complex analytical strategies and results with clarity and scientific authority to both technical and non-technical audiences, including senior leadership
• Manage competing priorities and resources to deliver quality scientific outputs within program timelines

Benefits

• Competitive benefits, services and programs that provide employees with the resources to pursue their goals, both at work and in their personal lives
• Health Coverage: Medical, pharmacy, dental, and vision care
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP)
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support
• Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
• Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
• Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day
• All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees