Data Scientist - Environment and Disease Modeling

Summary

Syngenta is a global Ag Tech powerhouse, headquartered in the United States, focused on shaping the future of agriculture. They are seeking a Data Scientist - Environment and Disease Modeling to support plant epidemiology and disease science by building predictive models for environmental and disease incidence, collaborating with various teams to provide actionable insights.

Responsibilities

• 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

Skills

• 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
• Experience with data visualization tools (R Shiny, Tableau, or equivalent) is a plus

Qualifications

Must Haves

• 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

Nice to Haves

• Experience with data visualization tools (R Shiny, Tableau, or equivalent) is a plus

Benefits

• 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.