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Statistical Genetics Jobs in California (NOW HIRING)

23andMe is looking for a quantitative scientist with extensive experience in population genetics and statistical modeling of human genetics data to join our R&D team. You will leverage your expertise ...

23andMe is looking for a quantitative scientist with extensive experience in population genetics and statistical modeling of human genetics data to join our R&D team. You will leverage your expertise ...

Required : • Experience in functional or single cell genomics and/or statistical genetics • Strong experience in modern computational statistics and machine learning • Bachelor's degree and ...

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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:
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.

Principal Scientist, Translational Genetics

Cytokinetics, Inc.

South San Francisco, CA • On-site

$202K - $236K/yr

Full-time

Re-posted 5 days ago


Job description

Cytokineticsis a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction.

At Cytokinetics, each team member plays an integral part in advancing our mission to improve the lives of patients. We are seeking tenacious, compassionate, and collaborative individuals who are driven to make a positive impact.

We are seeking a highly motivated and skilled Principal Scientist, Translational Genetics to join our growing team. The successful candidate will play a critical role in analyzing large-scale genetic and genomic datasets to identify and select therapeutic targets for cardiovascular and muscle diseases. This position requires a strong foundation in statistical genetics, bioinformatics, AI/ML methods, genomics and a passion for translating genetic insights into clinical applications.

Responsibilities:

Data Analysis:

  • Perform genome-wide association studies (GWAS), fine-mapping, and other statistical genetics analyses using large-scale genomic datasets (e.g., UK Biobank, All of Us, FinnGen, etc.).

  • Analyze and integrate multi-omics data (genomics, transcriptomics, proteomics, metabolomics) to identify causal variants and pathways associated with cardiovascular diseases.

  • Develop and apply statistical models to predict disease risk and treatment response based on genetic and clinical data.

  • Design and evaluate AI/ML methods for large-scale imaging-derived phenotyping (e.g., cardiac MRI, DEXA)

  • Conduct Mendelian randomization studies to infer causal relationships between genetic variants and cardiovascular traits.

Target Identification and Validation:

  • Identify and prioritize genetic targets for therapeutic intervention based on statistical and functional evidence.

  • Contribute to the design and analysis of genetic studies to validate drug targets and biomarkers.

  • Collaborate with experimental biologists and clinicians to translate genetic findings into preclinical and clinical research.

Bioinformatics and Data Management:

  • Develop and maintain bioinformatics pipelines for processing and analyzing genomic and electronic health records (EHR) data.

  • Manage and curate large-scale genetic and clinical datasets.

  • Utilize and develop statistical software and tools for data analysis and visualization (e.g., R, Python, PLINK, Hail).

Collaboration and Communication:

  • Collaborate with cross-functional teams, including biologists, clinicians, and computational scientists.

  • Present research findings at internal meetings, scientific conferences, and in peer-reviewed publications.

  • Contribute to the preparation of regulatory documents and grant applications.

  • Maintain detailed and organized records of all analyses.

Qualifications:

  • Education: Ph.D. in Statistical Genetics, Human Genetics, Bioinformatics, Computational Biology or a related field with

  • Experience:

    • 6+ years of experience in the biotech or pharmaceutical industry (or relevant post-doctoral experience) and demonstrated impact on project progression

    • Strong expertise in analyzing large-scale genomic datasets, including GWAS and sequencing data.

    • Proficiency in statistical programming languages (R, Python) and bioinformatics tools.

    • Experience with Mendelian randomization and multi-omics data integration is highly desirable.

    • Prior experience in the cardiovascular / cardiometabolic therapeutic domain is strongly preferred.

  • Skills:

    • Strong analytical and problem-solving skills.

    • Excellent communication and presentation skills.

    • Ability to work independently and as part of a team.

    • Strong organizational and time management skills.

    • Ability to learn new skills quickly.

Preferred Qualifications:

  • Experience with cloud computing platforms (e.g., AWS, Google Cloud) and biobank research analysis platforms (e.g., DNAnexus RAP, All of Us Workbench)

  • Experience with machine learning and deep learning methods, and strong interest in applying these methods to biological problems

  • Experience with multidimensional and longitudinal data analysis in biology or medicine

  • Publications in peer-reviewed journals related to statistical genetics and cardiovascular disease.

Please submit your CV, a cover letter outlining your research experience and interests, and a list of publications

#LI-ONSITE

Pay Range:

In the U.S., the hiring pay range for fully qualified candidates is $202,500.00 - $236,250.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors.

Our employees come from different backgrounds, and we celebrate those differences. We are looking for the best candidates for our open roles, but do not expect applicants to meet every qualification in order to be considered. If you are excited about what you could accomplish at Cytokinetics and believe you can add value to our team, we would love to hear from you.

Please review ourGeneral Data Protection Regulation (GDPR) policyPRIOR to applying.

Our passion is anchored in robust scientific thinking, grounded in integrity and critical thinking. We keep the patient front and center in all we do - all actions and decisions are in service of the patient and their caregivers. We champion integrity, ethics, doing the right thing, and being our best selves.

Fraud Warning: How to Identify Impersonated Cytokinetics Job Postings and Offers

Recently, there have been fraudulent employment offers being sent to candidates on behalf of Cytokinetics. Please be advised that all legitimate offers from Cytokinetics will come directly from our official email domain (Cytokinetics.com) and will only be made after completing a formal interview process.

Here are some ways to check for authenticity:

  • We do not conduct job interviews through non-standard text messaging applications

  • We will never request personal information such as banking details until after an official offer has been accepted and verified

  • We will never request that you purchase equipment or other items when interviewing or hiring

  • If you are unsure about the authenticity of an offer, or if you receive any suspicious communication, please contact us directly attalentacquisition@cytokinetics.com

Please visit our website at:www.cytokinetics.com

Cytokinetics is an Equal Opportunity Employer