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Variant Scientist Jobs in California (NOW HIRING)

LatchBio

AI Biologist - Variant

San Francisco, CA · On-site +1

$120K - $180K/yr

Bioinformatics Engineer - Variant As molecular data generation and frontier model intelligence ... scientists across 150+ R&D labs to handle data from instrument-to-insights. We're seeking a ...

EdenRoc Sciences

Scientific Sales, Oncology

San Diego, CA · On-site

$80K - $120K/yr

This role will support our genomic variant products and services business unit-directly targeting ... Position Requirements: • Bachelor of Science • 3-5+ years' proven track record selling into the ...

DutchTech

Analytical Scientist I

Emeryville, CA · On-site

$120 - $140/hr

The Analytical Science team is looking for a talented scientist to collaboratively work with our R& ... Have illustrated the ability to develop, execute, and interpret aggregation and charge variant ...

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How much do variant scientist jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for variant scientist in California is $46.07, according to ZipRecruiter salary data. Most workers in this role earn between $33.43 and $58.38 per hour, depending on experience, location, and employer.

What is a variant scientist?

Variant Scientists are professionals who analyze genetic variants—differences in DNA sequences—to determine their significance in health and disease. They interpret genomic data, often from whole-genome or exome sequencing, to assess whether specific variants may cause or contribute to medical conditions. Their work is crucial in clinical genetics, precision medicine, and biomedical research, helping guide patient diagnosis and treatment. Variant Scientists collaborate with clinicians, bioinformaticians, and laboratory personnel to provide accurate and actionable genetic insights.

What does a variant scientist do?

As a variant scientist, you work for a research laboratory in a university or a medical facility to test and study variations of genes and the effects they have on human development. As part of your duties, you aid in the development of new tests to discover gene abnormalities, perform analysis on patient samples to identify possible mutations, and record your findings to assist in scientific research. You also have heavy reporting responsibilities that may require in-depth computer and writing skills, the ability to analyze data, and strong attention to detail. In this role, you may cater to a specific health field, like pediatrics or oncology.

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

To thrive as a Variant Scientist, you need a solid background in genetics, molecular biology, and bioinformatics, typically supported by an advanced degree such as a PhD or MSc in a related field. Familiarity with next-generation sequencing (NGS) platforms, variant annotation tools, and data analysis software like GATK or ANNOVAR is essential. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex genetic data and collaborate with multidisciplinary teams. These skills ensure accurate variant interpretation, drive discoveries, and support precision medicine initiatives.

What are some common challenges faced by variant scientists in interpreting genetic data, and how are these typically addressed within a team?

Variant Scientists often encounter challenges such as distinguishing between benign and pathogenic variants, managing large volumes of sequencing data, and staying updated with rapidly evolving genetic databases. These challenges are typically addressed by collaborating closely with bioinformaticians, clinical geneticists, and laboratory personnel to review findings and validate interpretations. Regular team meetings, use of standardized classification guidelines like ACMG, and leveraging advanced software tools help ensure accurate and consistent variant analysis.
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Variant Scientist jobs near you
Infographic showing various Variant Scientist job openings in California as of August 2026, with employment types broken down into 83% Full Time, 12% Part Time, and 5% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $95,835 per year, or $46.1 per hour.

Bioinformatics Engineer - Variant

San Francisco, CA • On-site

Jobtailor
See more jobs at Jobtailorexternal

$150 - $210/hr

Other

Posted 7 days ago

Job description

  • You’ll design, build, and evaluate LLM benchmarks for genomic analysis - spanning read alignment, assembly, variant calling, GWAS, causal inference, and multiomics integration.
  • Your benchmarks and evaluations will set the bar for how well AI agents can serve as analysis partners for scientists working with human genetics data.
  • You’ll own the full evaluation pipeline: choosing datasets, defining failure modes, writing grading scripts, and shipping evaluations that measure real capability.
  • Your work directly impacts how LLMs reason through genomic problems.
Requirements
  • 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 through publications or industry work
  • Deep expertise in at least one of: population genetics, statistical genetics, clinical genomics
  • Fluency with genotyping workflows: variant calling, fine-mapping, Mendelian randomization
Core Competencies

Demonstrates expertise in designing and evaluating LLM benchmarks for genomic analysis, with a strong focus on human genetics data and proficiency in genotyping workflows. Capable of managing the full evaluation pipeline, including dataset selection and performance measurement.

Highest-signal resume keywords
  • Master's Or PhD In Bioinformatics
  • 3-5 Years Research Experience In Genomics
  • Deep Expertise In Population Genetics
  • Fluency With Genotyping Workflows
  • Experience With Variant Calling
ATS Optimization Keywords Hard Skills
  • Genomic Analysis
  • Read Alignment
  • Assembly
  • Variant Calling
  • GWAS
  • Causal Inference
  • Multiomics Integration
  • Statistical Genetics
  • Clinical Genomics
Industry Keywords
  • Human Genetics Data
  • Evaluation Pipeline
  • Datasets
  • Failure Modes
  • Grading Scripts
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