Senior Technical Product Manager – Human Biology

xebiacee; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

xebiacee is seeking a senior technical program manager to lead strategic programs for human biology R&D, bridging product, engineering, data, and science teams. You will shape roadmaps, own backlogs, and drive cloud-based data platforms from discovery to launch.

The role demands deep experience in life sciences, multi-omics data, and agile delivery, with fluency in coordinating across data, platform, UI/UX, and AI/ML disciplines. A strong foundation in cloud services and governance is required.

Qualifications

• 8+ years in technical program management, product management, or technical delivery in cloud data or informatics.
• Strong background in life sciences with ability to engage researchers and data scientists.
• Hands-on software/data engineering fundamentals and cloud platforms knowledge.

Responsibilities

• Own and prioritize product backlogs across biological data repos and pipelines.
• Drive programs through strategy, requirements validation, architecture review, and launch.
• Translate scientific needs into user stories, criteria, and technical requirements.
• Coordinate dependencies across data eng, platform, UI/UX, AI/ML, and scientific teams.
• Run discovery and feedback loops with researchers to shape roadmaps.
• Define data models, metadata standards, and governance practices.

Skills

Technical program management

Life sciences domain knowledge

Cloud data platforms

Backlog ownership

Agile/Scrum

Jira & Confluence

cross-functional leadership

Tools

GCP (BigQuery, Workflows, Vertex AI, Cloud Run, Cloud Storage)

SQL/NoSQL databases

Job description

Role overview

Lead strategic technical programs that support human biology R&D, working at the intersection of product, engineering, data, and scientific teams. The role blends program management, backlog ownership, and life-sciences domain knowledge to turn complex research needs into scalable cloud and data platforms from discovery through launch.

Responsibilities

• Own and prioritize product backlogs spanning biological data repositories, analytical pipelines, and search/visualization platforms across multiple workstreams
• Drive programs through the full lifecycle, from strategy and requirements validation to architecture review and launch, including UAT and release readiness
• Translate scientific and business needs into user stories, acceptance criteria, and actionable technical requirements
• Coordinate dependencies across data engineering, platform engineering, UI/UX, AI/ML, and scientific knowledge engineering teams
• Run continuous discovery, user research, and feedback loops with researchers and R&D stakeholders to shape roadmaps
• Define data models, metadata standards, and FAIR-aligned governance practices, and address security, compliance, and traceability requirements

Requirements

• 8+ years in technical program management, product management, or technical delivery on cloud-based data or scientific informatics platforms
• Strong background in life sciences, biopharma, biotech, or a closely related scientific domain, with the ability to engage fluently with cell biologists, computational biologists, and data scientists
• Solid grasp of human biological data and multi-omics types (transcriptomics/RNA-seq, proteomics, functional assays), plus biological ontologies and FAIR data principles
• Hands-on technical foundation in software engineering, data engineering, data pipelines, APIs, distributed systems, and modern cloud platforms
• Practical experience with GCP services such as BigQuery, Workflows, Vertex AI, Cloud Run, and Google Cloud Storage, and with SQL/NoSQL databases
• Expertise in Agile, Scrum, and hybrid delivery models, with advanced use of Jira, Confluence, and requirements traceability

Nice to have

• Experience in pharmaceutical or regulated environments, including GxP and 21 CFR Part 11
• Familiarity with AI/ML platforms and MLOps concepts
• Background in HPC, large-scale data processing, or HPC-to-cloud migration, plus GCP architecture for scientific workloads
• Knowledge of in vitro cell models, high-throughput phenomics, or translational research workflows
• Human data governance expertise covering privacy, reproducibility, lineage, and audit readiness
• Vendor management experience and GCP certifications such as Professional Cloud Architect or Professional Data Engineer