Breeding Data Scientist Intern - Plant Genomics

Corteva Agriscience; Johnston (IA); On-site; USD 28,000 - 39,000; Part time

Job summary

Vylor seeks a Breeding Data Scientist Intern to help advance plant breeding through data-driven insights. You will work with scientists to design strategies, analyze genomic and phenotypic data, and translate results into practical tools used by breeders.

The role emphasizes collaboration across teams, building reproducible analyses, and applying quantitative methods to breeding decisions in a global context.

Qualifications

• MS or PhD student in Plant Breeding, Quantitative Genetics, Agronomy, Data Science, or related fields.
• Strong problem-solving ability to derive actionable results from data.
• Experience with phenotypic and genomic datasets in R or Python.
• Familiarity with statistical modeling, ML, or simulations in biology.
• Interest in turning breeding/genomics needs into usable software/tools.
• Ability to collaborate across cross-functional teams.

Responsibilities

• Collaborate with North America Technology Deployment to design and evaluate breeding strategies.
• Navigate genomic, phenotypic, and environmental data to improve selection decisions.
• Interact with breeders to understand technology-driven breeding impacts.
• Communicate findings and recommendations to diverse audiences.

Skills

Analytical skills

Data analysis in R/Python

Cross-functional collaboration

Communication of findings

Breeding knowledge

Education

MS or PhD student in Plant Breeding, Quantitative Genetics, Agronomy, Data Science, or related fields

Tools

R

Shiny

Python

Git

Job description

Vylor seeks a Breeding Data Scientist Intern to help advance plant breeding through data-driven insights. You will work with scientists to design strategies, analyze genomic and phenotypic data, and translate results into practical tools used by breeders.

The role emphasizes collaboration across teams, building reproducible analyses, and applying quantitative methods to breeding decisions in a global context.