Senior Technical Program Manager - Scaled Human Biology

Role overview A Senior Technical Program Manager is needed to drive strategic programs on a scaled human biology data platform serving researchers, cell biologists, computational biologists, and data scientists inside a pharmaceutical R&D environment. The role blends deep technical program leadership with scientific fluency, operating within a hybrid delivery model that combines waterfall-style governance with agile execution to accelerate R&D outcomes.

Responsibilities - Own product backlog, prioritization, and planning across multiple workstreams including a high-scale biological data repository, analytical pipelines, and a search and visualization UI. - Drive continuous discovery, lead products through governance checkpoints from strategy alignment to launch, and validate business value through platform metrics, user feedback, and scientific experimentation. - Translate ambiguous scientific requirements into well-defined user stories, acceptance criteria, and Product Development Plans. - Shape data models, metadata standards, and FAIR data compliance in collaboration with scientific knowledge engineering teams. - Manage dependencies across data engineering, platform engineering, UI/UX, AI/ML, and scientific teams while coordinating multi-vendor partners. - Champion AI use cases, NLP-based analytics, and GenAI-powered documentation to accelerate delivery and inform backlog prioritization. - Maintain rigorous Jira, Confluence, RAID, and governance documentation and participate in sprint planning, retrospectives, and Product Strategy Reviews.

Requirements - 8+ years of technical program or product management experience delivering cloud-based data platforms or scientific informatics systems. - Proven track record managing large, cross-functional programs across many engineering teams and scientific stakeholders. - Deep familiarity with multi-omics data types such as transcriptomics, proteomics, and functional assays, and biological ontology frameworks. - Strong grounding in FAIR data principles, human data governance, patient privacy, and regulated life sciences environments. - Expert user of Jira and Confluence for backlog management, traceability, and requirements documentation. - Strong understanding of Agile, Scrum, and hybrid delivery models, with excellent stakeholder, communication, and conflict resolution skills.

Nice to have - Translational research familiarity, such as benchmarking model systems against disease endophenotypes. - Exposure to AI/ML workflows or vector embedding generation in biological research. - Background in quantitative systems pharmacology or computational biology. - Experience with multi-vendor coordination, data sharing agreements, and contract dependency management. - Familiarity with enterprise life sciences software vendors and platforms. - Track record of platform modernization, technical debt reduction, portfolio rationalization, and cloud cost optimization.

Benefits and work setup - Partnership-driven hybrid delivery environment inside a pharmaceutical R&D program, evaluated through quarterly 360° reviews and objective business metrics covering user satisfaction, cycle time, cloud cost efficiency, and AI innovation velocity.