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Statistical Genetics Jobs in California (NOW HIRING)

LatchBio

AI Biologist - Variant

San Francisco, CA · On-site +1

$120K - $180K/yr

Master's or PhD in bioinformatics, genetics, biology, statistics, or related field * 3-5 years of hands-on research experience analyzing genomics datasets (especially human data), demonstrated ...

MyOme

Machine Learning Scientist

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

Background in statistical genetics a plus Why Work at MyOme? * You want to help people in your life and the rest of the planet by contributing to the development of cutting edge healthcare products ...

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Statistical Genetics information

What does a statistical geneticist do?

A statistical geneticist analyzes genetic data using statistical methods to identify genetic factors associated with traits or diseases. They often work with large datasets, employ software tools like R or Python, and collaborate with researchers to interpret genetic information for research or clinical purposes.

What are the key skills and qualifications needed to thrive as a statistical geneticist, and why are they important?

To thrive as a Statistical Geneticist, you need a strong background in genetics, statistics, and bioinformatics, often supported by an advanced degree (such as a PhD) in genetics, statistics, or a related field. Expertise with analytical tools like R, Python, PLINK, and genome-wide association study (GWAS) software, as well as familiarity with large-scale genetic datasets, is typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for interpreting data and collaborating with multidisciplinary teams. These skills are crucial for generating meaningful genetic insights, advancing research, and ensuring accurate analysis in complex genetic studies.

How to become a statistical geneticist?

To become a statistical geneticist, typically a candidate needs a bachelor's degree in genetics, statistics, or a related field, followed by a master's or Ph.D. in statistical genetics, bioinformatics, or computational biology. Developing skills in programming languages like R or Python, understanding genetic data analysis, and gaining experience through research or internships are also important steps.

What are some typical collaborative projects a statistical geneticist might work on within a multidisciplinary research team?

Statistical Geneticists frequently collaborate on projects involving genome-wide association studies (GWAS), analysis of large-scale sequencing data, and development of new statistical methods for genetic data interpretation. These projects often require close teamwork with bioinformaticians, laboratory scientists, clinicians, and data analysts to design studies, interpret findings, and translate genetic discoveries into clinical or biological insights. Such collaborations offer opportunities to contribute specialized statistical expertise while learning from other disciplines, ultimately advancing both scientific understanding and career growth.

What is the difference between Statistical Genetics vs Bioinformatics?

AspectStatistical GeneticsBioinformatics
Required CredentialsDegree in Genetics, Statistics, or related fieldsDegree in Computer Science, Bioinformatics, or related fields
Work EnvironmentResearch labs, academic institutions, healthcare settingsResearch labs, biotech companies, healthcare institutions
Industry UsageGenetic research, disease association studies, population geneticsGenomic data analysis, sequence alignment, data management

Statistical Genetics focuses on analyzing genetic data using statistical methods to understand inheritance and disease associations, while Bioinformatics emphasizes developing computational tools for managing and interpreting biological data. Both roles often collaborate but serve distinct functions within genetic research and healthcare industries.

What is statistical genetics?

Statistical genetics is a field of study that combines statistics and genetics to analyze and interpret genetic data. It focuses on understanding the genetic basis of traits and diseases by applying statistical methods to data from genome-wide association studies, family studies, and population genetics. Statistical geneticists develop models and tools to map genes that contribute to complex traits, estimate heritability, and predict genetic risk. Their work supports advances in personalized medicine, agriculture, and evolutionary biology.
What are popular job titles related to Statistical Genetics jobs in California? For Statistical Genetics jobs in California, the most frequently searched job titles are:
What job categories do people searching Statistical Genetics jobs in California look for? The top searched job categories for Statistical Genetics jobs in California are:
What cities in California are hiring for Statistical Genetics jobs? Cities in California with the most Statistical Genetics job openings:
Statistical Genetics jobs near you
Infographic showing various Statistical Genetics job openings in California as of August 2026, with employment types broken down into 2% As Needed, 75% Full Time, 19% Part Time, 2% Temporary, 1% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Scientist / Senior Scientist, Machine Learning for Health Risk Prediction

23andMe

Palo Alto, CA • On-site

Full-time

Re-posted 2 days ago

Job description

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 accommodations-ext@23andme.com. 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

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