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Data Science Plant Breeding Jobs (NOW HIRING)

PhD in plant breeding, animal breeding, quantitative genetics, statistical genetics, data science, or a related scientific discipline; or an MS with 5+ years of relevant experience; Strong background ...

PhD in plant breeding, animal breeding, quantitative genetics, statistical genetics, data science, or a related scientific discipline; or an MS with 5+ years of relevant experience; Strong background ...

PhD in plant breeding, animal breeding, quantitative genetics, statistical genetics, data science, or a related scientific discipline; or an MS with 5+ years of relevant experience; * Strong ...

PhD in plant breeding, animal breeding, quantitative genetics, statistical genetics, data science, or a related scientific discipline; or an MS with 5+ years of relevant experience; * Strong ...

$94K - $135K/yr

PhD in plant breeding, animal breeding, quantitative genetics, statistical genetics, data science, or a related scientific discipline; or an MS with 5+ years of relevant experience;Strong background ...

... Plant Science, Agronomy, or a related field. * Experience in a plant breeding or agricultural research environment. * Demonstrated experience managing and curating large data sets. * Advanced ...

... science, plant breeding, plant pathology, or related fields * Demonstrated organizational and time management skills * Supervisory experience * Demonstrated ability keeping records of research data ...

... science, plant breeding, plant pathology, or related fields * Demonstrated organizational and time management skills * Supervisory experience * Demonstrated ability keeping records of research data ...

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Data Science Plant Breeding information

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$37.5K

$122.7K

$196.5K

How much do data science plant breeding jobs pay per year?

As of Jun 7, 2026, the average yearly pay for data science plant breeding in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How do data scientists in plant breeding typically collaborate with agronomists and geneticists to drive research outcomes?

Data scientists in plant breeding often work closely with agronomists and geneticists to analyze large datasets generated from field trials and genomic studies. This collaboration involves regular meetings to discuss experimental design, data collection protocols, and interpretation of results. Data scientists contribute their expertise in statistical modeling and machine learning, while agronomists and geneticists provide domain-specific insights, ensuring that analyses are both scientifically rigorous and practically applicable. Such teamwork is essential for developing improved crop varieties and optimizing breeding strategies.

What is the difference between Data Science Plant Breeding vs Agronomist?

AspectData Science Plant BreedingAgronomist
Required CredentialsDegree in Data Science, Plant Breeding, or related fields; knowledge of statistics and programmingDegree in Agronomy, Agriculture, or related fields; expertise in crop management and soil science
Work EnvironmentResearch labs, data analysis centers, field trials with data focusFieldwork, research farms, agricultural consulting
Industry UsageUsed in biotech companies, research institutions, seed companiesUsed in farming, crop production, agricultural extension services

Data Science Plant Breeding focuses on applying data analysis and machine learning to improve plant breeding programs, while Agronomists work directly with crop management and soil health in the field. Both roles support agriculture but differ in their core activities and skill sets.

What is data science in plant breeding?

Data science in plant breeding involves using advanced statistical analysis, machine learning, and computational tools to analyze large datasets related to plant traits, genetics, and environmental factors. This approach helps breeders identify patterns and make data-driven decisions to improve crop yield, disease resistance, and other desirable characteristics. By integrating genomics, phenomics, and environmental data, data science accelerates the breeding process and increases the accuracy of selecting superior plant varieties.

What are the key skills and qualifications needed to thrive as a Data Science Plant Breeding professional, and why are they important?

To thrive as a Data Science Plant Breeding professional, you need expertise in plant genetics, quantitative analysis, statistical modeling, and a strong background in biology or agronomy, often supported by advanced degrees. Proficiency with data analytics tools (such as R, Python, and SAS), bioinformatics platforms, and experience handling large-scale genomic datasets are typically required. Strong problem-solving skills, collaboration, and effective communication are crucial soft skills for translating complex data into actionable breeding strategies. These skills and qualities are essential for driving innovation, improving crop traits, and supporting data-driven decision-making in agricultural research.
High Throughput Phenotyping Research Associate - Strawberry Breeding

High Throughput Phenotyping Research Associate - Strawberry Breeding

Driscoll's, Inc.

Watsonville, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

About the Opportunity
The High Throughput Phenotyping Research Associate - Strawberry Breeding will support the strawberry breeding program in executing research-level breeding trials on time, with high precision and accuracy, in a safe and compliant manner, to generate high-quality data for identifying superior-performing products during the growing season. The role contributes to cultivar development, germplasm curation, and advancement of key traits that improve yield, flavor, and fruit quality to meet market demands. The position reports to the local Strawberry Breeding Scientist and contributes data and insights to support breeding decisions, applying and refining established analytical approaches to enhance data use across the organization.
In alignment with Driscoll's long-term breeding strategy, this role will support the implementation and continuous improvement of high-throughput phenotyping approaches under the direction of the breeding program, including scalable data collection systems, imaging technologies, and AI-enabled tools to support phenotypic data capture and integration into genomic prediction workflows. The position is expected to execute breeding operations with high precision while contributing to improvements in phenotyping efficiency and data quality.
Responsibilities
Field, Greenhouse & Trial Operations
• Support execution of specialized breeding trials under the guidance of the Northern District Strawberry Breeder.
• Coordinate field, greenhouse, nursery, and farming activities to ensure timely and accurate trial execution.
• Evaluate seedlings, collect phenotypic data, maintain trial organization and inventory, and support advancement decisions.
• Supervise and coordinate seasonal staff during key evaluation, harvest, and operational periods.
Phenotyping, Lab & Data Activities
• Execute fruit quality and postharvest evaluations including Brix, pH, flavor, shelf life, bruising, rot/mold, and color assessments across breeding stages.
• Support field layout, planting, phenotyping, harvest, tissue collection, and sample coordination for genotyping and genomic selection workflows.
• Drive adoption and implementation of high-throughput phenotyping approaches to enable AI- and data-driven decision-making within the breeding program.
• Support high-throughput phenotyping initiatives, including imaging validation studies, trait evaluation, and integration of phenotypic data into breeding analytics and decision-support pipelines.
• Apply established imaging and AI-enabled tools to support phenotyping, data quality assessment, and efficient data collection workflows.
• Maintain fruit lab organization, equipment, labeling systems, and phenotyping workflows.
• Validate datasets and support timely delivery of high-quality data through established analytical and statistical approaches.
• Prepare summaries, reports, and analyses to support advancement, selection, and breeding decisions.
Collaboration & Communication
• Communicate work status, priorities, and operational needs effectively across teams.
• Assist with varietal newsletters, presentations, reports, grower communications, and occasional breeding program tours.
• Collaborate across the global strawberry breeding network by sharing updates, learnings, and operational support as needed.
Other Duties
• Perform additional job-related duties to support breeding operations, research initiatives, and team objectives.
Candidate Profile
• Bachelor's degree with ~5 years of relevant experience, in Agronomy, Crop Science, Plant Breeding, Statistics, or Data Science.
• 2-4 years of experience in applied research, agronomy, plant breeding support, phenotyping, spatial analytics, or agricultural data science.
• Strong understanding of agronomy, plant physiology, experimental design, and field trial execution.
• Skilled in data management and analysis tools; familiarity with genotyping workflows and breeding databases is preferred.
• Strong attention to detail and commitment to accurate, high-quality data collection and reporting.
• Demonstrated ability to coordinate field activities, supervise seasonal staff, and manage multiple priorities in dynamic field and research environments.
• Effective communication, organizational, and cross-functional collaboration skills.
• Proactive mindset with initiative to improve workflows, protocols, and operational efficiency.
• Flexible and capable of working effectively across field, greenhouse, laboratory, and office environments.
• Commitment to safety, teamwork, and alignment with Driscoll's values of passion, humility, and trustworthiness.
• Valid California driver's license and eligibility for company vehicle insurance.
• Valid passport and willingness to travel domestic and international as required.
Preferred Qualifications
• Familiarity with AI-enabled, image-based, or data-driven phenotyping tools and technologies.
• Exposure to statistical analysis, visualization, or programming tools such as R, Python, Tableau, GIS, or related platforms.
• Experience supporting multi-location agricultural or breeding trials.
• Familiarity with plant breeding, nursery operations, or genotyping workflows.
• Interest in improving phenotyping efficiency, standardization, and data quality through technology-driven approaches.
Compensation and Benefits
The following information is provided in good faith as a general description of the salary range and benefits for the position posted. The actual compensation offered to the successful candidate is dependent upon experience, skills, education, work location, internal pay equity, and other objective job-related factors.
Salary Range estimated for the High Throughput Phenotyping Research Associate - Strawberry Breeding role: $76,810.00/year to $95,000.00/year.
Driscoll's is committed to a culture of care and offers an attractive benefits package that varies between our locations. Benefits may include comprehensive medical, dental, and vision coverage, life insurance, and disability coverage for positions working more than 30 hours per week (US). Other benefits may include: 401(k) with employer match, profit-sharing participation, paid sick time, paid vacation, paid personal and family care leave, and a free Employee Assistance Program (EAP). More detailed information regarding the benefits package based on your geographic location will be shared during the application process.
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