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Genomic Data Science Jobs in California (NOW HIRING)

Hologic

Principal Bioinformatician

San Diego, CA · On-site

$129K - $216K/yr

Data Science & Bioinformatics * Build and maintain scalable pipelines for genomic data processing, annotation, and analysis. * Integrate public and proprietary datasets to inform assay design and ...

Hologic Inc.

Principal Bioinformatician

San Diego, CA · On-site

$129K - $216K/yr

Data Science & Bioinformatics * Build and maintain scalable pipelines for genomic data processing, annotation, and analysis. * Integrate public and proprietary datasets to inform assay design and ...

DD-Scientific Data

Scientific Data Engineer

Bodega Bay, CA

$135K - $163K/yr

Master's or PhD in Computer Science or related field, with 5 or more years of professional ... genomics, or protein design * Experience designing or working with structured data models, schemas ...

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Genomic Data Science information

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$16

$56

$80

How much do genomic data science jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for genomic data science in California is $56.07, according to ZipRecruiter salary data. Most workers in this role earn between $46.01 and $66.44 per hour, depending on experience, location, and employer.

What is genomic data science?

Genomic data science is an interdisciplinary field that focuses on analyzing and interpreting vast amounts of genetic and genomic data using computational and statistical methods. Professionals in this field use bioinformatics tools, machine learning, and data analysis techniques to uncover insights about genes, diseases, evolution, and biological processes. Genomic data scientists often work with large datasets from next-generation sequencing and collaborate with biologists, clinicians, and researchers to advance our understanding of genetics and its applications in medicine and research.

How does a genomic data scientist typically collaborate with multidisciplinary teams in research or healthcare settings?

Genomic Data Scientists often work closely with biologists, clinicians, statisticians, and software engineers to interpret complex genomic datasets. Collaboration usually involves translating biological questions into analytical tasks, developing and applying computational pipelines, and communicating findings in accessible terms. Regular meetings, shared project management tools, and cross-disciplinary workshops are common, fostering an environment where diverse expertise is integrated to advance research or clinical objectives. This collaborative approach not only enhances the quality of insights but also provides opportunities for professional growth and learning from adjacent fields.

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

To excel as a Genomic Data Scientist, you need a strong background in bioinformatics, genetics, and statistical analysis, typically supported by a degree in biology, computational science, or a related field. Familiarity with tools like Python, R, next-generation sequencing (NGS) platforms, and databases such as Ensembl is crucial, as is experience with cloud computing or high-performance computing environments. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are vital soft skills in this role. These competencies enable accurate data interpretation, effective collaboration, and innovative research that advances our understanding of genomics.

What is the difference between Genomic Data Science vs Bioinformatics?

AspectGenomic Data ScienceBioinformatics
Required CredentialsDegree in Data Science, Bioinformatics, or related fields; programming skillsDegree in Bioinformatics, Biology, or related fields; computational skills
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch labs, academic institutions, biotech firms
Industry UsageAnalyzing large genomic datasets, developing algorithmsSequence analysis, genome annotation, biological data interpretation
Common Search IntentData analysis in genomics, computational methods for geneticsGenomic sequence analysis, biological data processing

While both roles involve working with genomic data, Genomic Data Science focuses on applying data science techniques, machine learning, and statistical analysis to large genomic datasets. Bioinformatics emphasizes biological sequence analysis, genome annotation, and biological interpretation. Both fields often overlap but differ mainly in their core focus: data science methods versus biological data analysis.

What are popular job titles related to Genomic Data Science jobs in California?

For Genomic Data Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Genomic Data Science jobs in California look for?

The top searched job categories for Genomic Data Science jobs in California are:

Genomic Data Science jobs near you
Infographic showing various Genomic Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $116,623 per year, or $56.1 per hour.

Principal Bioinformatician

Hologic

San Diego, CA • On-site

$129K - $216K/yr

Full-time

Re-posted 10 days ago

Key responsibilities

  • Lead the strategy and execution of bioinformatics efforts for multiplex PCR assay design and optimization.

  • Develop and implement computational pipelines for primer and probe design, assay validation, and collaboration with wet-lab teams.

  • Design and deploy AI/ML models to predict assay performance, optimize conditions, and analyze amplification data.

Hologic rating

8.0

Company rating: 8.0 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

182nd of 499 rated machine equipment manufacturers

Job description


We are seeking an innovative and highly experienced Principal Scientist in Bioinformatics to lead the design, development, and optimization of advanced PCR-based multiplex assays using cutting-edge computational and AI-driven approaches. This role will combine deep expertise in molecular assay design, bioinformatics algorithms, and machine learning/AI to enable next-generation diagnostic and research solutions.
The ideal candidate will be a scientific leader in shaping the future of AI-driven molecular diagnostics, applied with your a proven track record of translating biological insights into scalable computational tools and robust assay designs, particularly in molecular diagnostics, such as multiplex PCR and qPCR.
This is an onsite role in San Diego, CA.
Key Responsibilities
  • Scientific Leadership
    • Lead the strategy and execution of bioinformatics efforts for multiplex PCR assay design and optimization.
    • Serve as a subject matter expert in AI driven assay design, including target selection, primer/probe design, specificity analysis, cross-reactivity minimization, and multiplex compatibility.
    • Drive innovation through the integration of AI/ML models to improve assay performance, design efficiency, and predictive accuracy.
    • Mentor and guide cross-functional scientists in bioinformatics, molecular biology, and data science.
  • Assay Development & Design
    • Develop and implement computational pipelines for high-quality primer and probe design for complex multiplex assays.
    • Optimize assays for sensitivity, specificity, and robustness across diverse sample types and targets.
    • Conduct in silico validation including thermodynamic modeling, sequence alignment, and off-target prediction.
    • Collaborate with wet-lab teams to iterate on assay performance using experimental feedback.
  • AI / Machine Learning Integration
    • Design and deploy AI/ML models to:
      • Predict primer/probe efficiency and multiplex interactions
      • Optimize assay conditions and configurations
      • Analyze amplification data and improve signal interpretation
    • Apply deep learning or probabilistic modeling approaches to sequence and assay design problems.
    • Stay current with emerging AI techniques and apply them to molecular diagnostics challenges.
  • Data Science & Bioinformatics
    • Build and maintain scalable pipelines for genomic data processing, annotation, and analysis.
    • Integrate public and proprietary datasets to inform assay design and validation.
    • Develop software tools to automate and standardize assay workflows.
  • Cross-functional Collaboration
    • Partner with R&D, computational biology, software engineering, and product teams to deliver end-to-end solutions.
    • Communicate complex computational concepts to non-technical stakeholders.
    • Support regulatory and clinical teams with analytical validation data.

Required Qualifications
  • Ph.D. in Bioinformatics, Computational Biology, Genomics, Molecular Biology, or a related field.
  • 8+ years of relevant experience (industry preferred), including leadership responsibility.
  • Deep expertise in:
    • Machine Learning / AI related to molecular diagnostics
    • PCR primer/probe design, including multiplex assay design principles
    • Bioinformatics tools (e.g., BLAST, alignment algorithms, sequence databases)
    • Programming (e.g., Python, R, or similar)
  • Demonstrated experience applying machine learning or AI to biological or genomic data.

Preferred Experiences
  • Experience with high-plex assays, digital PCR, qPCR, or NGS-based diagnostics.
  • Knowledge of thermodynamics of nucleic acid interactions and assay chemistry.
  • Familiarity with cloud computing and scalable pipelines (e.g., AWS, Azure, GCP).
  • Experience in regulated environments (e.g., CLIA, FDA, IVDD/IVDR).
  • Publication record or patents in assay development, bioinformatics, or applied AI.

Required Key Competencies
  • Strategic thinking and scientific leadership
  • Strong analytical and problem-solving skills
  • Innovation mindset with a focus on AI-enabled solutions
  • Excellent communication and collaboration skills
  • Ability to translate research into practical applications

The annualized base salary range for this role is $$129,700 to $216,200 and is bonus eligible. Final compensation packages will ultimately depend on factors including relevant experience, skillset, knowledge, geography, education, business needs, and market demand.
Why Hologic?
We are committed to making Hologic the company where top talent comes to grow. For you to succeed, we want to enable you with the tools and knowledge required and so we provide comprehensive training when you join as well as continued development and training throughout your career.
If you have the right skills and experience, apply today!
#LI-RF1 #Principal-level
Agency and Third Party Recruiter Notice:
Agencies that submit a resume to Hologic must have a current executed Hologic Agency Agreement executed by a member of the Human Resource Department. In addition, Agencies may only submit candidates to positions for which they have been invited to do so by a Hologic Recruiter. All resumes must be sent to the Hologic Recruiter under these terms or they will not be considered.
Hologic, Inc. is proud to be an Equal Opportunity Employer inclusive of disability and veterans.

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