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Bioinformatic Jobs in California (NOW HIRING)

As a Bioinformatics Engineer in the Content Development team, you will play a critical role in maintaining and extending QIAGEN's biomedical knowledge base by integrating new knowledge from public ...

Bioinformatics Analyst - CA

Irvine, CA · On-site

$70K - $85K/yr

We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines ...

As a Bioinformatics Engineer in the Content Development team, you will play a critical role in maintaining and extending QIAGEN's biomedical knowledge base by integrating new knowledge from public ...

They are seeking a talented Bioinformatics Analyst to implement and aid in the design and analysis of software and informatics pipelines for various data analyses to support pharmaceutical asset ...

Bioinformatics Analyst - CA

Irvine, CA · On-site

$70K - $85K/yr

We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines ...

We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines ...

Showing results 41-60

Bioinformatic information

See California salary details

$53.8K

$94.9K

$137.2K

How much do bioinformatic jobs pay per year?

As of Sep 3, 2026, the average yearly pay for bioinformatic in California is $94,910.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,900.00 and $108,100.00 per year, depending on experience, location, and employer.

What is a bioinformatic?

A bioinformatics job involves using computational tools and techniques to analyze biological data, such as DNA sequences, protein structures, and gene expression patterns. Professionals in this field develop algorithms, manage large datasets, and apply statistical methods to extract meaningful insights from complex biological information. Bioinformaticians work in areas like genomics, drug discovery, personalized medicine, and agricultural research, often collaborating with biologists and data scientists.

What does a bioinformatic do?

Bioinformaticians typically spend their days analyzing biological data, developing and optimizing algorithms, and interpreting results in collaboration with laboratory scientists and researchers. You may work on tasks such as processing large-scale sequencing data, maintaining databases, and creating custom scripts to support specific research projects. Regular meetings with biologists, data analysts, and software engineers are common to ensure seamless integration of experimental and computational tasks. The collaborative nature of the role means Bioinformaticians often contribute to publications, share findings with team members, and help troubleshoot complex data challenges.

What are the key skills and qualifications needed to thrive in the bioinformatic position?

To thrive as a Bioinformatician, you need a strong background in biology, computer science, and statistics, often supported by a relevant degree such as bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python, R, or Perl, experience using bioinformatics tools and databases, and knowledge of data visualization platforms are typically expected. Problem-solving, strong communication, and the ability to work collaboratively are valued soft skills in this position. These competencies are essential for efficiently analyzing complex biological datasets, deriving actionable insights, and contributing to multidisciplinary research teams.

Is bioinformatics well paying?

Bioinformaticians typically earn competitive salaries that vary by experience, education, and location. Entry-level positions often start around $60,000 to $80,000 annually, with experienced professionals earning over $100,000, especially in biotech or pharmaceutical industries. Skills in programming, data analysis, and familiarity with tools like R or Python can enhance earning potential.

Is it hard to get a job in bioinformatics?

Bioinformatics jobs can be competitive, often requiring strong skills in biology, computer science, and data analysis, along with experience in programming languages like Python or R. Candidates with relevant education, such as a degree in bioinformatics or related fields, and familiarity with tools like genomic databases and analysis pipelines tend to have better prospects.

What are the jobs in bioinformatics?

Jobs in bioinformatics include roles such as bioinformatics analyst, computational biologist, bioinformatics scientist, and data analyst. These positions typically involve analyzing biological data using programming skills, statistical tools, and software like R, Python, or specialized bioinformatics platforms. They are common in research institutions, pharmaceutical companies, and healthcare organizations.

What are the most commonly searched types of Bioinformatic jobs in California?

The most popular types of Bioinformatic jobs in California are:

What cities in California are hiring for Bioinformatic jobs?

Cities in California with the most Bioinformatic job openings:

Infographic showing various Bioinformatic job openings in California as of August 2026, with employment types broken down into 79% Full Time, 8% Part Time, 4% Temporary, and 9% Contract. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $94,910 per year, or $45.6 per hour.

Lead Bioinformatician (cfDNA Algorithms and Pipelines)

Natera

San Carlos, CA

Full-time

Posted 23 days ago


Natera rating

7.8

Company rating: 7.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

54th of 121 rated laboratories


Job description

Natera is seeking a Lead Bioinformatician to advance the algorithmic foundations of our diagnostic assays supporting Women's and Organ health. This is an individual contributor role. You will bring the genomics expertise the team needs to pull reliable signals out of sequencing data that is often ambiguous.

You will build the methodological foundations and implement the algorithms needed for detecting variants (SNVs, Indels, CNVs, SVs) that are hard to call accurately in low fraction (fetal, donor cfDNA) samples. The ideal candidate will have deep experience in algorithmic genomics, strong programming skills, and a passion for developing scalable, clinically impactful computational tools.

Primary Responsibilities:

Panel and Assay Science: Provide genomics algorithm insights to our expanded panel roadmap, including which genes are worth considering and why, working with Product, the Laboratory Directors, and Research, who own that decision jointly. Help define the approach for analytically difficult genes and assay edge cases, and weigh what is scientifically defensible against what is technically possible.

Caller Strategy and Method Development: Define the computational strategy for new targeted and special-purpose callers. Help decide when a new caller is justified and when an existing method should be extended instead. Prototype and benchmark new methods, and work with the engineering team to get methods into production.

Scientific Investigation and Escalation: Serve as a genomics consultant on complex production escalations, separating biological causes from analytical and pipeline ones. Recognize when a result looks suspicious because of where the reads came from and not because the analysis went wrong. Turn one-off investigations into durable rules and design changes that reduce repeat work.

Data Quality and Cross-functional Partnership: Act as bioinformatics liaison with Variant Management, Reporting, and Laboratory Operations on data quality, variant representation, and system integration. Provide the scientific rationale that the accountable Quality and Laboratory functions rely on when they decide a method is ready to deploy.

Ways of Working: Help define what correct looks like for AI-assisted scientific investigation, for example what an agent may and may not conclude from a region-level finding without a human signing off. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide the tooling and the ramp time.

What success looks like after a year:
  • Contributed to the scientific and bioinformatics rationale of product roadmaps.
  • Deployment-readiness criteria for new analysis methods exist and are in use, and you have contributed to at least one new or extended caller yourself.
  • You take on the bioinformatics aspects inside complex production investigations without waiting to be assigned them.
  • Other groups know they can bring genomics questions about our assays to you.
Qualifications:
  • Degree in Bioinformatics, Computational Biology, Bioinformatics, Human Genetics, or a related field. We do not require a Ph.D. or M.S.: equivalent depth built through work counts fully.
  • 4+ years analyzing short-read sequencing data for screening or diagnostic applications, preferably in a regulated, accredited, or production-adjacent setting. We count relevant experience from the point your work became substantially independent, however you got there.
  • Experience contributing to the bioinformatics workflows behind a sequencing assay or panel.
  • Experience seeing a complex investigation through to resolution across biological, analytical, and systems-level causes.
Knowledge, Skills, and Abilities:What we are screening for
  • Experience developing, validating, or benchmarking bioinformatics methods (e.g. SNVs, CNVs, SVs), particularly for analytically difficult regions.
  • Proficient in Python with demonstrated experience prototyping bioinformatics tools or callers.
  • Enough human genetics depth to contribute to the panel design: variant spectrum, population frequency, and where compromises on accuracy can (and cannot) be made.
  • Familiarity with identifying regions where short reads cannot be placed with confidence: homologous sequence and pseudogenes, low-complexity and repeat structure, and copy-number-heavy regions.
  • Experience contributing to study designs or performance criteria for a bioinformatics analysis method.
Strong candidates may also have
  • Direct non-invasive prenatal, reproductive, or carrier screening experience.
  • Experience with cfDNA, or with another application where the molecules you care about are a small minority of what was sequenced.
  • Experience developing algorithms for both short-read and long-read sequencing platforms (e.g., Illumina, ONT, PacBio).
  • Cross-functional credibility with genetic counseling, variant management, reporting, and production-adjacent groups.
  • Experience in an accredited or high-complexity laboratory, or familiarity with production support or escalation processes.

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