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Python Biology Jobs in Davis, CA (NOW HIRING)

Cramer Fish Sciences

Data Steward Technician

West Sacramento, CA · On-site

$24 - $30/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... biological or environmental sciences. The Data Steward Technician will assist in collecting ... Generate basic data summaries, tables, and figures using Excel, R, Python, or comparable software ...

All JobsPython Biology JobsPython Biology Jobs in Davis, CA

Python Biology information

See Davis, CA salary details

$14

$63

$93

How much do python biology jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for python biology in Davis, CA is $63.36, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $71.97 per hour, depending on experience, location, and employer.

What is the difference between Python Biology vs Bioinformatics Analyst?

AspectPython BiologyBioinformatics Analyst
Required CredentialsBiology degree, Python programming skillsBiology or related degree, Python and data analysis skills
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageData analysis, modeling biological systems using PythonAnalyzing biological data, developing pipelines, interpreting results

Python Biology focuses on applying Python programming to biological research, often emphasizing coding and data modeling. Bioinformatics Analysts combine biological knowledge with data analysis skills, including Python, to interpret complex biological datasets. Both roles require programming skills and work in similar environments, but Python Biology is more research and development-oriented, while Bioinformatics Analysts focus on data interpretation and analysis.

Is Python useful for biology?

Python is widely used in biology-related jobs for data analysis, modeling, and automation of research workflows. Skills in Python, along with knowledge of biological data formats and libraries like Biopython, are valuable for roles in bioinformatics, computational biology, and systems biology.

How do Python biology professionals typically collaborate with interdisciplinary teams in research settings?

Python Biology professionals often work closely with biologists, data scientists, and software engineers to analyze complex biological data. Collaboration usually involves translating biological questions into computational tasks, developing data pipelines, and presenting findings in a way that is accessible to both technical and non-technical stakeholders. Regular meetings and code reviews are common practices, ensuring that the software developed aligns with the scientific goals of the project. This interdisciplinary approach not only enhances research outcomes but also provides valuable learning and growth opportunities for team members.

What are the key skills and qualifications needed to thrive as a computational biologist specializing in Python?

To thrive as a Computational Biologist with a focus on Python, you need a strong background in biology, bioinformatics, and programming, typically supported by a degree in biological sciences, computer science, or a related field. Familiarity with Python libraries like Biopython, NumPy, and pandas, as well as experience with data analysis tools and version control systems such as Git, is essential. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting biological data and collaborating with interdisciplinary teams. These competencies enable accurate data analysis, innovative research, and effective teamwork in advancing biological discoveries.

What is a Python biologist?

A Python biologist is a professional who uses the Python programming language to analyze and interpret biological data. They often work in fields like bioinformatics, genomics, and computational biology, developing software tools to process large datasets such as DNA sequences or protein structures. Python biologists help translate complex biological problems into computational solutions, enabling researchers to gain insights that would be difficult to achieve manually.
What are popular job titles related to Python Biology jobs in Davis, CA? For Python Biology jobs in Davis, CA, the most frequently searched job titles are:
What job categories do people searching Python Biology jobs in Davis, CA look for? The top searched job categories for Python Biology jobs in Davis, CA are:
What cities near Davis, CA are hiring for Python Biology jobs? Cities near Davis, CA with the most Python Biology job openings:
Python Biology jobs near you

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

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