Data Scientist - Environment and Disease Modeling

Role Description

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. To support this mission, Syngenta is seeking a Data Scientist - Environment and Disease Modeling in Field, MN. This role will support the plant epidemiology and disease science within the Temperate Hub R&D organization. This role combines expertise in environmental data analysis, plant disease modeling, and geospatial analytics to advance management across the breeding pipeline. In this role you will:

• Build and apply predictive models for environment and disease incidence and severity.
• Link genotypic variation to disease susceptibility.
• Translate complex biological and environmental signals into actionable insights for breeders and agronomists.

The Data Scientist - Environment and Disease Modeling will partner closely with germplasm development teams, pathologists, and global R&D colleagues to deliver disease resistance insights that directly inform selection decisions—both within a season and across multiple years and environments.

Accountabilities:

• Develop and maintain disease progression models integrating weather, soil, and agronomic data to predict incidence and severity across crops and geographies within season and across years.
• Integrate environmental and geospatial datasets (climate layers, remote sensing, field location metadata) to characterize biotic and abiotic stress landscapes and support site-based decision making and location management.
• Compare controlled environment and field data for inoculated trials, partner with pathologists and breeders to curate high-quality datasets for model training and validation, and translate phenotypic disease observations into quantitative traits.
• Design reproducible, scalable pipelines for data ingestion, QC, modeling, and visualization that can be deployed across the temperate hub breeding programs.
• Communicate findings and model outputs to scientific and non-scientific stakeholders through clear reports, dashboards, and/or presentations to support data-driven breeding strategy and management decisions.
• Collaborate with global teams to align environmental and disease modeling methods with broader platform architecture and data standards.

Qualifications

• Master’s or PhD in Plant Pathology, Epidemiology, Quantitative Genetics, Computational Biology, Data Science, or a related field.
• Strong foundation in plant epidemiology and disease biology, including familiarity with major temperate crop pathogens and their interaction with host genetics and environment.
• Demonstrated experience with environmental and geospatial data: weather station integration, climate variables, GIS tools, remote sensing products, or spatial interpolation methods.
• Proficiency in statistical and machine learning modeling, including mixed models, survival analysis, or spatiotemporal models applicable to epidemiological data.
• Proficient programming skills in R and/or Python. Familiarity with SQL, version control, and cloud-based development environments.

Requirements

• PLEASE NOTE: Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This includes, but is not limited to, OPT, CPT, and H-1B visa holders.

Benefits

• A culture that celebrates belonging and collaboration, 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.
• Full Benefit Package (Medical, Dental & Vision) that starts your first day.
• 401k plan with company match, Profit Sharing & Retirement Savings Contribution.
• Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits.