Sr. Product Manager

DNAnexus•Mountain View, CA

3d•$175,000 - $190,000•Hybrid

About The Position

DNAnexus is seeking a Senior Product Manager to own the product direction for the data consumption and analytics layer of a modern omics platform for large-scale omics research and clinical workflows. This is a senior individual contributor role at the intersection of enterprise platform experiences and life sciences. You will define the product experience for how users query and analyze omics data at scale, how enterprise teams integrate with their existing analytical tooling, and how users and agentic AI systems will consume analytics capabilities on DNAnexus. You will work closely with software engineers, bioinformatics experts, design partners, and customers at leading pharma and biotech organizations. Your success will be measured by the adoption, scientific credibility, and commercial traction of the capabilities you own. The ideal candidate has a strong platform PM track record with some meaningful exposure to the omics or life sciences domain, and thrives in a technically demanding, customer-facing environment. You bring rigor and speed in equal measure. You will report to the Head of Product.

Requirements

7+ years in product management, including meaningful time owning platform or infrastructure products with real users and measurable outcomes.
Applied PM experience in data warehousing and distributed analytics frameworks (Spark, Trino, DuckDB, BigQuery, or similar).
Platform and technical depth. Fluency in distributed compute concepts and API design for technical users. You can read system architecture diagrams and engage in API discussions without engineering arbitrating every call.
Both zero-to-one and mature-product experience. You've shipped new products from scratch and operated products with existing customer obligations.
Cross-functional influence. You drive alignment across engineering, security, domain experts, and commercial teams through clarity and credibility.
Executive communication. You can turn ambiguous technical and commercial information into board-ready narratives. You have excellent executive presentation and communication skills. You are comfortable identifying, navigating, and managing diverse interests (sometimes competing) of key stakeholders in your product plans and decisions.
Experience in regulated data environments is strongly preferred. Ideally life sciences, genomics, or clinical research.
Biological literacy is strongly preferred. Foundational knowledge of molecular biology and genomics. Concepts of variants vs. genes, RNA vs. DNA, gene expression and objectives of common translational analyses (GWAS, gene expression analysis) are not entirely foreign to you.

Nice To Haves

Familiarity with the contemporary omics platform ecosystem (Hail, Databricks, TileDB, hyperscaler-native solutions).
Demonstrated ability to define researcher workflows from publications, customer interviews, and SME input.
Hands-on background as a computational biologist, bioinformatician, or research scientist having carried out common translational analyses (GWAS, burden tests, cohort phenotyping, transcriptomics/expression analysis).
Experience designing agent-friendly APIs or building products at the intersection of AI and life sciences.
Pricing experimentation. Experience with consumption-based, tiered, or seat-based platform pricing models.

Responsibilities

Product strategy: In partnership with the Head of Product, translate product vision for the omics platform into a credible multi-quarter roadmap for molecular data consumption and analytics.
Define researcher and developer experiences: define and iterate on how computational biologists, data engineers, and enterprise teams query, analyze, and extract insights from omics data at scale — including distributed compute workflows, built-in statistical functions, biology specific algorithms, and domain-specific APIs (FHIR, Python).
Lead interoperability requirements: specify the integration layer that connects the omics platform to enterprise analytical environments, and other platforms in the omics ecosystem (e.g. SageMaker, Databricks). Define GUI experiences and consumption-layer APIs that serve diverse user types.
Define agent-ready platform requirements: in partnership with the AI PM, specify what analytics APIs and data structures must look like to support agentic users - enabling AI agents to plan, execute, and recover from complex bioinformatics workflows autonomously.
Define benchmarking requirements: specify the researcher queries, analytical functions, and performance metrics that engineering and the product design need to optimize for. Translate the user’s flows and needs into concrete requirements for system benchmarking.
Lead customer and design partner programs: In partnership with the Head of Product, run structured discovery sessions with pharma and biotech partners. Translate customer insights directly into PDLC/SDLC artifacts and roadmap initiatives.
Drive cross-functional execution: serve as the product manager for your engineering pod. Author high-quality Epics and User Stories with clear acceptance criteria and embedded product health metrics representative of user needs. Track and report initiative health proactively.
Communicate to leadership: turn product, customer, and competitive insights into clear narratives for the Head of Product and senior leadership.