Associate Director, Data Science
Princeton - NJ - USAll locationsPrinceton - NJ - USSeattle 400 Dexter - WA - USBrisbane - CA - USCambridge Crossing - MA - USLos Angeles, CA Hybrid
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About the role
This is a new position. You will join a cutting-edge Drug Development Data Science and Advanced Analytics (DSAA) team as a senior scientific and technical leader, driving data science strategy and execution to advance the global drug development process. We are looking for a seasoned data scientist with a strong computational, statistical, and biological background and a demonstrated track record of leading analytical strategy, driving methodological innovation, and translating complex, multi-modal data into impactful scientific insights that inform clinical development decisions. As an Associate Director, you will provide scientific leadership across diverse data types generated in drug development — including clinical trial data, genomics, proteomics, imaging, flow cytometry, and other biomarker modalities — driving both the strategic direction and hands-on execution of data science efforts across early-to-late phase drug development programs. You will define and champion analytical frameworks, methodological standards, and scalable approaches that elevate the quality and impact of data science across the organization, while serving as a key scientific partner to Biostatistics leads, Translational and Clinical Scientists, and senior cross-functional stakeholders. This position may include management of a small team of data scientists. We are looking for a technically excellent, scientifically influential, and strategically minded practitioner.
What you'll bring
- Ph.D. in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, Computer Science, or related field) and 6+ years of academic/industry experience
- or Master's Degree in a relevant quantitative field and 8+ years of industry experience
- Demonstrated mastery in data science and statistical analysis with data generated from clinical trials or electronic health records, with a strong track record of delivering impactful results in a pharma R&D context
- Significant experience leading the development and application of statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes
- Proven expertise in the application of AI/ML and proficiency in Python, R, SQL, and cloud platforms (e.g., AWS, Azure, Databricks)
- Deep familiarity with clinical trial design, drug development processes, and the role of biomarkers and data science in regulatory and clinical decision-making
- Demonstrated ability to define and drive analytical strategy across multiple concurrent programs, balancing scientific rigor with practical delivery
- Significant track record of driving statistical and AI/ML innovation, with a perspective on leveraging emerging approaches to expedite drug development and address complexities of novel data types
- Demonstrated ability to lead, mentor, and collaborate with multidisciplinary teams, and to manage multiple concurrent high-priority programs with competing timelines
- 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