SPD Data Scientist Intern
Join Vylor—Powering the Future of Agriculture
At Vylor, we’re advancing agriculture through breakthrough science—combining elite germplasm, cutting-edge biotech, and next-generation expertise in gene editing and molecular breeding. Our portfolio includes trusted industry brands like Pioneer®, Brevant®, and Hoegemeyer®, delivering performance farmers rely on.
Join us to help scale innovation globally and shape what’s next in crop science.
Are you passionate about advancing plant breeding through innovative science and technology? Do you thrive at the intersection of fieldwork and analytics, and enjoy turning complex biological questions into practical breeding solutions? If so, you might be a great fit for our SPD Breeding Data Scientist Intern position.
Vylor is seeking a graduate student with an interest in applying data science skills in plant breeding and quantitative genetics. In this role, you will interact with breeding scientists, statisticians, and domain experts to enhance breeding strategies and accelerate genetic gain.
At Vylor, we are committed to transforming agriculture through innovation. Join us in shaping the future of plant breeding and delivering improved varieties to farmers around the world.
In this role, you will:
- Partner closely with scientists in the North America Technology Deployment team to design, build, and evaluate breeding strategies that leverage both traditional and modern quantitative methods.
- Learn to navigate genomic, phenotypic, and/or environmental data within breeding pipelines to improve selection accuracy and decision-making.
- Interact with breeders to understand how technologies affect breeding decisions.
- Communicate findings and recommendations clearly to relevant audiences.
Job Qualifications:
- MS or PhD student in Plant Breeding, Quantitative Genetics, Agronomy, Data Science, or related fields.
- Excellent problem-solving skills and the ability to explore analytic solutions by asking the right questions, analyzing data, and producing actionable results.
- Experience working with phenotypic and genomic datasets in R or Python for data analysis and visualization.
- Familiarity with statistical modeling, machine learning, or simulation techniques as applied to biological systems.
- Interest in translating breeding and genomics needs into practical, usable software or analytical tools.
- Interest in building collaboration and communication skills, while working in cross-functional teams.
What will set you apart:
- Proficiency in R, ideally including experience building interactive applications (e.g., Shiny) or other web-based tools.
- Experience building reproducible analyses and pipelines (e.g., version control such as Git, workflow automation, or scripting to refresh analyses as new data arrives).
- Hands-on experience with genomic selection, GWAS/marker-effect estimation, or environmental modeling in a breeding context.
- Understanding of breeding program design, selection theory, and genetic evaluation methods.
- Experience applying machine learning and/or artificial intelligence to breeding problems.
- A passion for applying science to solve real-world agricultural challenges.
Location:
Preferred location for this position is Johnston, IA
Are you a good match? Apply today! We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team.