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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Biostatistics Scientist (Plant Science - **Company:** Sakata Seed America, Inc. - **Location:** Woodland, CA, United States - **Experience:** Starter - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Data Analysis, Bioinformatics, Cloud Computing, Computational Biology, Databases, Data Cleansing, Data Sharing, Data Visualization, Linux, R (Programming Language), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, SAS (Software), Scientific Computating, Git, Data Management - **Published:** September 11, 2026 - **Apply:** https://www.thejobnetwork.com/job/b0ae2cac-008e-4eb8-9ce1-c4589f4b5dc6/biostatistics-scientist-plant-science ## About the Role * 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., * 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., * 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. ## Description 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., 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., Works under the guidance of senior scientists, project leads, and cross-functional research teams ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Branch your database like your code: How schema changes and pull requests go hand in hand](https://www.wearedevelopers.com/videos/350-branch-your-database-like-your-code-how-schema-changes-and-pull-requests-go-hand-in-hand) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [A Guide to Green Tech and Green IT Careers](https://www.wearedevelopers.com/magazine/374-a-guide-to-green-tech-and-green-it-careers) - [Got AI ideas but no money? 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