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Plant Bioinformatics Jobs in California (NOW HIRING)

TPIRC

Research Associate - Plant Proteomics

Long Beach, CA · On-site

$75K - $95K/yr

Familiarity with bioinformatics tools, protein databases, and software for proteomic data analysis and protein annotation. * Experience working with food proteins, plant-derived bioactive compounds ...

TPIRC

Research Associate - Plant Proteomics

Long Beach, CA · On-site

$75K - $95K/yr

Familiarity with bioinformatics tools, protein databases, and software for proteomic data analysis and protein annotation. * Experience working with food proteins, plant-derived bioactive compounds ...

The Rockridge Group

Software Engineer II

Emeryville, CA · On-site

$112K - $154K/yr

Software Engineer II RESEARCH AND DEVELOPMENT - BIOINFORMATICS AND SOFTWARE ENGINEERING We are ... Client X manufactures sustainable plant-derived ingredients using fermentation-based technology to ...

LatchBio

AI Biologist - Metagenomics

San Francisco, CA · On-site +1

$120K - $180K/yr

Master's or PhD in microbiology, microbial ecology, bioinformatics, biology, or related field * 3+ ... Plant, soil, or environmental microbial ecology * Experience interpreting microbiome data in ...

LatchBio

AI Biologist - Metagenomics

San Francisco, CA · On-site

$120 - $180/hr

Master's or PhD in microbiology, microbial ecology, bioinformatics, biology, or related field * 3+ ... Plant, soil, or environmental microbial ecology * Experience interpreting microbiome data in ...

Reliant

Real Life Church Residency

Valencia, CA

Our grandiose vision is to plant 30 more churches and/or multisite campuses by 2030 (30 by 30). Keys to Success: * Have a relationship with Christ that is evident through personal time with God ...

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Plant Bioinformatics information

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$5

$43

How much do plant bioinformatics jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for plant bioinformatics in California is $43.14, according to ZipRecruiter salary data. Most workers in this role earn between $43.12 and $43.12 per hour, depending on experience, location, and employer.

What is a plant bioinformatics?

A Plant Bioinformatics job involves using computational tools and biological data to study plant genetics, genomics, and molecular biology. Professionals in this field analyze large datasets to improve crop breeding, understand plant traits, and enhance agricultural sustainability. They work with sequencing data, develop algorithms, and use machine learning to solve biological problems. Plant bioinformaticians collaborate with geneticists, biologists, and agronomists to advance plant science and improve food production.

What are the key skills and qualifications needed to thrive in plant bioinformatics, and why are they important?

To thrive in Plant Bioinformatics, you need expertise in biology, genetics, statistics, and computer science, often backed by an advanced degree in bioinformatics, plant science, or a related field. Familiarity with bioinformatics software (e.g., BLAST, Galaxy), programming languages (Python, R), and data analysis tools is highly valued. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills in this field. These qualifications are crucial because the work involves interpreting complex biological data and collaborating across scientific disciplines to drive research and innovation.

What are some typical challenges faced by professionals in plant bioinformatics, and how do they contribute to the team's goals?

Professionals in plant bioinformatics often navigate challenges such as managing large-scale genomic data, keeping up with rapid advancements in sequencing technologies, and ensuring data accuracy for meaningful biological interpretation. They work closely with laboratory scientists, computational biologists, and agronomists to translate raw data into actionable insights for crop improvement or fundamental research. Overcoming these challenges requires both technical expertise and collaboration, making plant bioinformatics a dynamic and rewarding field where your contributions can directly impact agricultural innovation and scientific understanding.

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

The most popular types of Plant Bioinformatics jobs in California are:

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

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

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

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

Plant Bioinformatics jobs near you
Infographic showing various Plant Bioinformatics job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $89,740 per year, or $43.1 per hour.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago

Key responsibilities

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.

Job description


JOB SUMMARY

The Biostatistics Scientist supports applied statistical analysis, quantitative genetics, and breeding analytics for vegetable crop research programs. This entry-level role contributes to genomic, phenotypic, and field-trial data analysis under the guidance of senior scientists, managers and cross-functional project teams. The position helps develop reliable, reproducible analytical workflows that improve trait evaluation, marker-assisted selection, genomic prediction, and data-driven breeding decisions.

Key Responsibilities

Statistical Analysis, Quantitative Genetics & Genomic Prediction

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.
  • Apply standard statistical and quantitative genetics methods, such as mixed models, heritability estimation, genetic correlations, and basic genomic prediction approaches.
  • Assist with evaluating model performance, prediction accuracy, and data quality across populations, environments, and breeding stages.
  • Contribute to analyses that help breeders understand trait variation, experimental results, and selection opportunities.
  • Document methods, assumptions, code, and results clearly to support reproducibility and team review.

Molecular Marker & Trait Analytics

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.
  • Assist molecular and breeding teams with data summaries for marker development, marker deployment, and trait evaluation projects.
  • Support quality control of genotypic and phenotypic datasets, including data cleaning, formatting, consistency checks, and basic exploratory analysis.
  • Help prepare selection metrics, trait summaries, and visualizations that integrate multiple sources of breeding data.
  • Translate analytical results into concise summaries that can be reviewed by breeders, molecular scientists, and project teams.

Genomic, Phenotypic & Field Trial Data Analysis

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.
  • Develop and maintain reproducible scripts for data quality control, statistical analysis, visualization, and reporting.
  • Contribute to the improvement of analytical templates, reporting workflows, and shared data practices in collaboration with bioinformatics and data teams.

Project Support & Cross-Functional Collaboration

  • Support analytical components of breeding, trait development, molecular marker, and technology projects.
  • Collaborate with breeders, phenotyping, molecular biology, bioinformatics, and data teams to understand project objectives and data requirements.
  • Prepare clear technical summaries, tables, figures, and presentations to communicate results to internal stakeholders.
  • Learn and apply current methods in biostatistics, quantitative genetics, breeding analytics, and reproducible scientific computing.


Required Qualifications

Education

  • PhD in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field; industry experience a plus
    or
  • MS in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field with 0–2 years of relevant academic, internship; industry experience a plus


Experience & Technical Skills

  • Foundational training in statistics, biostatistics, quantitative genetics, plant breeding, computational biology, or related analytical disciplines.
  • Experience with statistical analysis of biological, genomic, phenotypic, field-trial, or experimental datasets through graduate research, internships, or applied projects.
  • Working knowledge of statistical programming in R, Python, SAS, or similar tools.
  • Good understanding of experimental design, mixed models, regression, data visualization, and reproducible analytical workflows.
  • Experience with molecular markers, genomic data, plant breeding concepts, or trait analysis is desirable.
  • Ability to learn new methods, manage multiple analytical tasks, and deliver accurate results with guidance.
  • Strong attention to detail, scientific curiosity, communication skills, and willingness to collaborate across disciplines.

Preferred Qualifications

  • Research experience in plant breeding, seed industry research, agricultural biotechnology, or applied life-science data analysis.
  • Experience in genomic prediction, QTL mapping, GWAS, marker-assisted selection, or trait discovery workflows.
  • Familiarity with breeding databases, phenotyping systems, laboratory information systems, or integrated data platforms.
  • Experience preparing figures, tables, dashboards, or technical reports for scientific or cross-functional audiences.
  • Exposure to cloud-based, Linux, Git, or high-performance computing environments for data analysis.
  • Interest in applying AI, machine learning, and modern statistical methods to practical breeding and research questions.

Competencies & Behaviors

  • Demonstrates curiosity, initiative, and accountability in learning new analytical methods and scientific workflows.
  • Applies statistical methods carefully, with attention to data quality, assumptions, and reproducibility.
  • Works collaboratively with scientists from breeding, molecular biology, phenotyping, bioinformatics, and data teams.
  • Communicates analytical results clearly to both technical and non-technical audiences.
  • Manages assigned tasks effectively, asks timely questions, and follows through on deliverables.
  • Contributes to a culture of scientific rigor, continuous improvement, teamwork, and practical problem solving.

Reporting Structure

  • Reports to Senior Biotech Manager

Works under the guidance of senior scientists, project leads, and cross-functional research teams

BENEFITS:

Health & Wellness
Medical, Dental & Vision Insurance
Monthly Wellness Stipend
Employee Assistance Program (EAP)

Employee Philanthropic Giving Program 

Disability Insurance (plans vary by location)


Financial Benefits
401(k) Program + Company Match
Profit Sharing Program (via 401(k)

Holiday Bonus

Performance Incentive Bonus Program
Tuition Reimbursement

529 College‑Savings Plan
Company-Paid Basic Life & AD&D Insurance


Time Off & Flexibility
Paid Vacation
Paid Sick Leave
15 Paid Company Holidays
2 Floating Holidays 

Birthday Off