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Bioinformatics Data Analyst Jobs in California (NOW HIRING)

GATC Health

Bioinformatics Analyst - CA

Irvine, CA · On-site

Responsibilities : • Prep and Process data through GATC platform based on customer or internal ... bioinformatics, computer science or similar. • Experience analyzing complex multi-omic datasets ...

GATC Health

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 ... Prep and Process data through GATC platform based on customer or internal end user requirements.

GATC Health

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 ... Prep and Process data through GATC platform based on customer or internal end user requirements.

GATC Health

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 ... Prep and Process data through GATC platform based on customer or internal end user requirements.

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All JobsBioinformatics Data Analyst JobsBioinformatics Data Analyst Jobs in California

Bioinformatics Data Analyst information

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$45

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How much do bioinformatics data analyst jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for bioinformatics data analyst in California is $45.22, according to ZipRecruiter salary data. Most workers in this role earn between $35.58 and $48.41 per hour, depending on experience, location, and employer.

What is a bioinformatics data analyst?

Bioinformatics Data Analysts are professionals who use computational tools and methods to analyze biological data, such as genomic sequences or protein structures. They work at the intersection of biology, computer science, and statistics to interpret complex datasets and draw meaningful insights for research or clinical applications. Their work supports areas like drug discovery, personalized medicine, and evolutionary biology. Typically, they collaborate with biologists, software engineers, and statisticians to solve complex biological problems. Strong analytical skills and proficiency with data analysis software are essential for this role.

How do bioinformatics data analysts collaborate with researchers and other team members?

Bioinformatics Data Analysts often work closely with biologists, clinicians, and software engineers, acting as a bridge between experimental research and computational analysis. Collaboration usually involves interpreting experimental data, discussing analytical approaches, and presenting findings in a way that's accessible to non-technical stakeholders. Regular team meetings and project updates are common, and strong communication skills are essential for translating complex data insights into actionable information for the broader research team. This multidisciplinary teamwork fosters innovation and ensures that analyses align with the goals of larger research projects.

What are the key skills and qualifications needed to thrive as a bioinformatics data analyst?

To thrive as a Bioinformatics Data Analyst, a solid background in biology, statistics, and programming (often with a degree in bioinformatics, computational biology, or a related field) is essential. Proficiency with tools such as R, Python, SQL, and bioinformatics software like BLAST or Bioconductor, as well as experience with large datasets and relevant certifications, is typically required. Strong analytical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, meaningful biological insights, and successful project outcomes in research or clinical settings.

What is the difference between Bioinformatics Data Analyst vs Bioinformatics Scientist?

AspectBioinformatics Data AnalystBioinformatics Scientist
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldsMaster's or PhD in Bioinformatics, Computational Biology, or related fields
Work EnvironmentData analysis teams, research labs, healthcare settingsResearch projects, development of algorithms, scientific publications
Employer & Industry UsageBiotech companies, healthcare institutions, research organizationsAcademic institutions, biotech firms, pharmaceutical companies
Common Search & ComparisonOften compared for data analysis roles in bioinformaticsMore research-focused, involved in algorithm development

Bioinformatics Data Analysts primarily focus on analyzing biological data using existing tools, while Bioinformatics Scientists develop new algorithms and conduct research. Both roles require strong computational skills, but the Scientist role typically involves more advanced research and innovation.

What are popular job titles related to Bioinformatics Data Analyst jobs in California?

For Bioinformatics Data Analyst jobs in California, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Data Analyst jobs in California look for?

The top searched job categories for Bioinformatics Data Analyst jobs in California are:

What cities in California are hiring for Bioinformatics Data Analyst jobs?

Cities in California with the most Bioinformatics Data Analyst job openings:

Bioinformatics Data Analyst jobs near you
Infographic showing various Bioinformatics Data Analyst job openings in California as of August 2026, with employment types broken down into 71% Full Time, 8% Part Time, 4% Temporary, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $94,060 per year, or $45.2 per hour.

Bioinformatics Data Scientist (Part-time/Temporary)

Artiva Biotherapeutics, Inc.

San Diego, CA • On-site

$55 - $65/hr

Temporary

Posted 15 days ago

Job description

About Artiva:

We are a clinical-stage biotechnology company focused on developing natural killer (NK) cell-based therapies. Our mission is to develop effective, safe, and accessible cell therapies for patients with devastating autoimmune diseases. We aim to develop therapies that patients and physicians can utilize in a community setting. Our lead product candidate,AlloNK, is a non-genetically modified, cryopreserved NK cell therapy being evaluated in combination with B-cell targeted monoclonal antibodies (mAbs). We believe the compelling cell killing properties of NK cells, when combined with mAbs for targeting, creates an opportunity to generate potentially transformative therapies.

For more information, visitwww.artivabio.com.


Position Summary:

Artiva Biotherapeutics is seeking a part-time/temporary Bioinformatics Data Scientist to help garner biological insights from multimodal biological data. You will design and maintain bioinformatics pipelines, generate insights, and build automated dashboards and reports in collaboration with wet-lab scientists, clinician-researchers, and data engineers.


Responsibilities:

  • Design, develop, and maintain bioinformatics pipelines and workflows for diverse biomedical data types including bulk RNA-seq, scRNA-seq, proteomic, and flow cytometric data.
  • Perform multi-omics and biomarker analysis including quality control, normalization, batch correction, differential expression analysis, clustering, dimensionality reduction (PCA, UMAP, t-SNE), cell type annotation, comparative analysis, and pathway analysis.
  • Support data integration, curation, and lifecycle management including annotation, data ingestion, metadata capture, schema management, and provenance tracking. Enable reliable data movement from source systems into structured, analysis-ready formats.
  • Build and support interactive dashboards, visualization tools, notebooks, and reports enabling researchers and clinicians to explore multi-omics, clinical, and sequencing data. Support figure generation for quality control, differential expression, and pathway analyses. Translate complex computational findings into clear biological narratives.
  • Collaborate with multidisciplinary teams including wet-lab scientists, bioinformaticians, clinician-researchers, biostatisticians, data engineers, and IT personnel.


Required Qualifications:

  • Bachelor's or master's degree (preferred) in Computer Science, Data Science, Bioinformatics, Computational Biology, or related field, and demonstrated experience (typically 2+ years) in bioinformatics pipeline development and biological data science.
  • Proficiency in Python for analysis, scripting, data science, and visualization. Familiarity with biological computing and data science libraries (e.g., Scanpy, Pandas, NumPy, scikit-learn).
  • In-depth knowledge of modern tools and pipelines for processing, aligning, and analyzing multimodal NGS and omics data. Knowledge of standard bioinformatics data formats (FASTQ, FCS) and related processing tools.
  • Proficiency with at least one pipeline framework (e.g., Airflow, Snakemake, Nextflow).
  • Experience with a cloud computing environment (GCP, AWS, Azure). Proficiency with queryable databases (e.g., PostgreSQL, BigQuery). Ability to work with structured, semi-structured, and unstructured data across relational and data lake environments.
  • Awareness of data governance, privacy, and compliance requirements for clinical and research data.
  • Strong background in constructing statistical models, hypothesis testing, regression analysis, clustering, and dimensionality reduction techniques. Demonstrated experience with machine learning (ML) methods and applying ML techniques to biological and clinical datasets. Knowledge of differential expression analysis, pathway analysis, and statistical methods relevant to genomic data.


Preferred Qualifications:

  • Advanced Development Tools: Experience with frameworks for web application development (Django, Flask, RShiny, Streamlit, React). Experience with CI/CD pipelines.
  • Advanced Biomedical Domain Knowledge: Background in biomedical research, clinical research, immunology, or healthcare analytics.
  • Governance & Data Management: Experience with metadata management, data lineage, open-source code release, containerized analyses, and secure handling of de-identified or access-controlled research datasets.


Compensation: $55 - 65/hr. Exact compensation may vary based on skills and experience.


If all this speaks to you, come join us on our journey!


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