Scientist / Senior Scientist, Machine Learning for Health Risk Prediction

23andMe is hiring a quantitative scientist to build predictive models of human health from large-scale genetic, medical, and real-world data. In this hands-on, individual-contributor role, you'll design, develop, and validate risk-prediction models that combine genetic signal with rich EHR and other phenotypic data to predict the incidence, timing, and drivers of health outcomes. We're looking for someone to advance the state of the art of health risk prediction, integrating and extending beyond traditional GWAS and polygenic prediction in a real-world application.

With the world’s largest database of more than 11 million consented research participants, 23andMe is at the forefront of using human genetics to advance biomedical research and transform healthcare. Join us in helping people access, understand, and benefit from the human genome.

Who We Are

We are a group of individuals passionate about genetic discovery. 23andMe Research Institute is a nonprofit medical research organization that enables people everywhere to access their genetic information, learn about themselves, and participate in the world’s largest crowdsourced research initiative. The Institute aims to be the world’s most significant contributor to scientific advancement, uniting people with the common goal of improving health and deepening our understanding of DNA, the code of life.

What You’ll Do

• Build predictive models of health outcomes by integrating genomic data with high-dimensional, longitudinal phenotypic data, including electronic health records (EHR).

• Apply time-to-event and survival modeling to predict not just "if" but "when" health events are likely to occur.

• Use a broad toolkit of machine learning and statistical modeling techniques, integrating polygenic scores with non-genetic risk factors, to build risk models that meaningfully improve on what's possible today.

• Validate model performance against external, non-23andMe datasets such as UK Biobank and All of Us.

• Work in close collaboration with product, engineering, and clinical teams to deploy risk models in both direct-to-consumer and clinical settings.

• Communicate your work to both technical and non-technical audiences through discussion, presentations, and scientific conferences, taking ownership of the high-level motivation, interpretation, and application of your projects.

• Publish your work in peer-reviewed journals, demonstrating the utility of integrating genetics into health risk prediction in real-world settings.

What You’ll Bring

• PhD in statistics, biostatistics, epidemiology, computer science, statistical genetics, or a related quantitative field. Ideal candidates have a background that bridges quantitative modeling and biological expertise.

• Proven ability to act as the primary code author of your analyses and models, writing clear, well-organized, and reproducible code in Python or a similar language, and collaborating in a shared GitHub repository.

• Hands-on experience modeling electronic health record (EHR) or other longitudinal clinical data. Experience working with large biobanks such as UK Biobank or All of Us is a plus.

• A track record of applying machine learning and statistical modeling to large-scale, messy, real-world datasets to predict health outcomes. Strong candidates can demonstrate the translation of this modeling work into specific applications.

• Outstanding interpersonal, verbal, and written communication skills, including the ability to frame your research within the higher-level goals and context of a project.

• Working experience with concepts related to epidemiology and health risk prediction, such as absolute and relative risk, confounding, ascertainment bias, and survival bias.

• Deep expertise in statistical genetics is not required; you should be comfortable treating genetic data (e.g., polygenic scores) as one valuable input to integrate with non-genetic risk factors.

• Understanding of the clinical context in which risk predictions are used.

Strongly Preferred

• 1–5 years of postdoctoral or industry experience.

• Bay Area location, or willingness to relocate.

You don't need to meet every qualification to apply. If this work excites you and you meet most of what's here, we'd love to hear from you.

About Us

23andMe, headquartered in California, is a leading consumer genetics and research company. The company’s mission is to help people access, understand, and benefit from the human genome. 23andMe has pioneered direct access to genetic information as the only company with multiple FDA authorizations for genetic health risk reports. The company has created the world’s largest crowdsourced platform for genetic research, with 80 percent of its customers electing to participate. 23andMe research participants consent to research conducted by 23andMe which is overseen by an independent third-party Institutional Review Board (IRB) regulated under the ‘Common Rule’ (45 CFR part 46). More information is available at www.23andme.com/research.

At 23andMe, we value a diverse, inclusive workforce and we provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual’s race, color, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws. If you are unable to submit your application because of incompatible assistive technology or a disability, please contact us at [email protected]. 23andMe will reasonably accommodate qualified individuals with disabilities to the extent required by applicable law.

Please note: 23andMe does not accept agency resumes and we are not responsible for any fees related to unsolicited resumes. Thank you.

Pay Transparency

23andMe takes a market-based approach to pay, and amounts will vary depending on your geographic location. The salary range reflected here is for a candidate based in the San Francisco Bay Area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

San Francisco Bay Area Base Pay Range

$165,000-$220,000