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