Lead Product Manager (Consumer Health)

You own the AI Health Summary and the home screen of the health app it anchors. Partner teams own the data pipelines and the underlying science. You own the experience that ties them together The Summary and health home screen. What gets surfaced, how insights are framed, and the engagement and retention metrics that show it is working Data connection. The member-facing experience of connecting EHR and wearable data: the prompts, the value exchange, and connection rates. You own whether members find connecting their data worth it Genetic insights. Polygenic and clinical risk scores are among the most differentiated content in the Summary. You own which insights we focus on and how they are surfaced and made actionable Privacy and trust. How members see and control what they share. You own this as part of the experience and work with design, security, privacy, and legal to get it right Clinical and regulatory fit. Medical, regulatory, and legal decide what the product can claim. You build a strong product within those limits and flag when a feature needs review. Familiarity with FDA-regulated health products helps here Inform the strategy. Bring the evidence and the point of view that shapes where the Health product goes. You own the what and the why of what gets built Make the case, or kill it. Build the evidence for what to do and what to skip. The default is not to build; the bar is a clear argument that something is worth doing Own the metrics. Define what success looks like and use the data, including your own explorations, to judge whether it is working Lead cross-functionally. Bring research, engineering, analytics, design, and marketing along with you, largely without direct authority Stay close to the member. Understand what members need and want from their health, and let that drive the what and the why Benefits Comprehensive health, vision, and dental plans Family planning, support, and leave for parents Mental healthcare Student loan assistance Dog friendly office Flexible time off A working understanding of the machine learning lifecycle, from data and feature engineering through evaluation and deployment, enough to make good trade-offs with the teams building the models8+ years of product management experience, or equivalent, with a track record of launching consumer web and mobile products at scaleComfort working with clinical, regulatory, and legal partners, and judgment about when a health feature needs review before shipping. Familiarity with FDA-regulated products is a plusFluency with data; you understand data structures and can build dashboards (e.g. in Hex) to track product healthExperience shipping consumer products in a privacy-sensitive, regulated space (health, fintech, or similar). HIPAA or genetic-data experience is a strong plusYou use LLMs daily in your own workflowExperience in consumer health and in AI/ML-powered productsStrong communication; you can carry a product vision and work through technical trade-offs with engineers and executivesA technical or life-sciences degree (e.g., Computer Science, Engineering, Bioinformatics, Statistics, Biology) or equivalent experience; an MBA is a plusAbility to work from 23andMe’s mid-Peninsula, CA office a minimum of 3 days per weekHands-on experience building and launching AI/ML-powered products: LLMs, NLP, recommendation engines, or predictive modelingExperience with products built on large-scale, multimodal data (genomic, clinical, behavioral)Fluency translating probabilistic or risk-based outputs, such as polygenic or clinical risk scores, into something a non-expert can understand and act onExperience partnering with a BD or integrations function to land third-party data into a consumer product (EHR or wearables a plus)Interest in working closely with researchers building on novel science #J-18808-Ljbffr 23andMe