Role Overview
This position is for a technically grounded scientific leader who thrives at the intersection of data science and life sciences R&D. You will play a central role in shaping how scientific data is structured, analyzed, and applied across biopharma workflows. Your work will directly influence the development of intelligent systems that accelerate research and improve decision-making in drug development.
Key Responsibilities
- Design and implement data architectures that support AI/ML applications in scientific contexts
- Translate scientific challenges into scalable data solutions through close collaboration with domain experts
- Conduct in-depth data exploration to uncover patterns and optimize research workflows
- Develop prototypes and demonstrations that validate new technical approaches
- Communicate insights effectively to both technical and non-technical audiences
- Provide strategic guidance to scientists on data-driven methods to enhance research outcomes
- Build reusable, extensible models that increase the value of scientific data assets
Qualifications
You bring advanced training in life sciences and substantial industry experience working with complex scientific datasets. A PhD with seven or more years, or a Master’s with ten or more years in the field is required. You have a proven ability to lead AI/ML initiatives in cloud environments and a history of delivering data solutions that generalize across use cases.
Experience working alongside product teams, engineers, and scientists is essential. You are comfortable advising on technical direction and have a demonstrated ability to bridge scientific needs with data architecture. A commitment to continuous learning and a mindset of ownership are critical to success in this role.
Technology & Environment
The role leverages AI/ML frameworks, cloud platforms, and advanced data modeling techniques to solve real-world scientific problems. You’ll work within a culture that values initiative, collaboration, and deep technical rigor. The environment emphasizes speed, adaptability, and alignment with core operating principles that guide decision-making.
Work Environment
This is a locally based position in Boston, requiring on-site presence. You will collaborate daily with interdisciplinary teams focused on advancing the future of lab data systems and AI-enabled scientific discovery.
