Applied Analytics Intern

Company Description

Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yields of crops. High-quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs. 

Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions.  

Syngenta Seeds is headquartered in the United States. 

Job Description

We invite you to help us shape the future of agriculture. At Syngenta, we believe every employee has a role to play in safely feeding the world and taking care of our planet. To support that challenge, the Applied Analytics team is looking for an intern who will work alongside our team to explore and quantify environmental features which impact yield, yield variability and data quality on a within-field basis to improve the optimal placement of trials through environmental risk mitigation. In this role, you will have the unique opportunity to explore the intersection of plant breeding and geospatial analytics and help drive operational improvements to help shape the future of Syngenta’s breeding and testing strategy.

As an intern at Syngenta, you will work alongside some of the brightest minds in the industry, and work on real projects finding real solutions. Work with us and you’ll get:

• Competitive wages ($40 hourly salary rate, depending on experience) 
• Ongoing career development resources & mentorship from scientific experts
• Meaningful projects that solve novel and interesting scientific problems
• Estimated Duration: May 2026 – August 2026
• Location:  Research Triangle Park, NC | Malta, IL | Slater, IA

You Will:

• Work with large field trial datasets to understand field variability from a quantitative genetics’ standpoint.
• Integrate traditional field datasets with large-scale environmental data in a geospatial context.
• Evaluate and identify the most important environmental variables and their relative impact on data quality.
• Improve existing models to define areas of risk within a geographic area.
• Work along side.
• Learn how to develop novel solutions which balance theory with the practicalities of working at industrial scale.
• Engage with stakeholders to communicate key results.
• The intern will operate in accordance with Syngenta Health, Safety, & Environmental (HSE) standards.

Qualifications

What You Must Have:

• Student must be currently pursuing a M.S. or Ph.D. in Plant Breeding, Quantitative Genetics, Agronomy, Data Science, or related fields.
• All applicants must be eligible to work in the US.
• Must be a current student continuing education upon completion of the internship term (May 2026 through August 2026).
• Demonstrated proficiency in one or more modern programming languages (Python, R etc.) and familiarity with SQL data queries.
• Scientific curiosity and passion for creative problem solving.
• Ability to communicate complex ideas and results in a clear and actionable manner.
• Exceptional interpersonal skills, comfortable working independently and as part of a team.
• Proactive approach to assigned objectives and goals.
• Prior experience with analyzing field trials and geospatial data is strongly desired.

Additional Information

What We Offer:

• A culture that celebrates diversity & inclusion, promotes professional development, and strives for a work-life balance that supports the team members. Offers flexible work options to support your work and personal needs. 
• Syngenta has been ranked as a top employer by Science Journal. 
• Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI 

Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. 

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