Overview In this role you drive data science, AI and digital health initiatives within Immunology R&D, shaping strategies and translating capabilities into practical solutions. You will partner across DDSAI and Immunology teams to advance data-enabled opportunities, accelerating research and decision making. You'll work with clinical and scientific partners to design scalable analytics, evaluate new tech, and communicate strategic guidance. This is a chance to impact tomorrow's therapies through cross-functional collaboration and innovative data solutions.
Compensation / Benefits- competitive base pay
- annual performance bonus
- medical/dental/vision insurance
- life insurance
- short- and long-term disability
- retirement plan (401(k
Responsibilities- Contribute to Immunology R&D DDSAI priorities across projects and collaborations
- Define, evaluate, and execute high-impact data science, digital health, and AI initiatives aligned with Immunology R&D goals
- Co-design data science use cases, develop roadmaps from pilot to scale, and identify reusable capabilities
- Understand imaging, digital health, clinical, and real-world data assets and align use cases with datasets and partners
- Map workflows to identify process improvements, automation, and future-state solutions
- Collaborate with platform and engineering teams to build scalable, interoperable data capabilities
- Evaluate emerging technologies (e.g., generative AI, agentic workflows) for impact on R&D
- Support portfolio intelligence by identifying new data assets and capabilities for decision making
- Prepare analyses and communications for technical and leadership forums to inform decisions
- Perform additional DDSAI tasks supporting broader R&D objectives
Key requirements- Master's degree in engineering, mathematics, or related scientific discipline with 4 years of relevant experience
- 4 years of experience in pharmaceutical R&D, biotechnology, healthcare, data science, digital health, AI, analytics, or related field
- Proven ability to work in cross-functional/matrixed environments
- Experience translating scientific or business needs into data/AI-enabled solutions
- Experience assessing and applying AI technologies, including generative AI and agentic systems
- Strong problem-solving, communication, organization, and stakeholder engagement skills
- Familiarity with healthcare datasets (clinical, imaging, real-world data, biomarkers)
- Cross-functional collaboration
- Strong communication
- Stakeholder engagement
- Python
- R
- SQL
