Logo for Syngenta

Data Scientist - Environment and Disease Modeling

Role overview

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
  • Demonstrated experience with environmental and geospatial data
  • Proficiency in statistical and machine learning modeling

Responsibilities

  • Develop and maintain disease progression models integrating weather, soil, and agronomic data
  • Integrate environmental and geospatial datasets to support site-based decision making
  • Design reproducible, scalable pipelines for data ingestion, QC, modeling, and visualization
  • Communicate findings and model outputs to scientific and non-scientific stakeholders

About the company

Syngenta  logo

Syngenta

Agricultural Tech & Precision Agriculture

Syngenta is one of the world’s leading agriculture companies. Our ambition is to help safely feed the world while taking care of the planet. We aim to improve the sustainability, quality and safety of agriculture with world class science and innovative crop solutions. Our technologies enable millions of farmers around the world to make better use of limited agricultural resources. Syngenta is part of Syngenta Group with 49,000 people in more than 100 countries and is working to transform how crops are grown. Through partnerships, collaboration and The Good Growth Plan we are committed to accelerating innovation for farmers and nature, striving for carbon neutral agriculture, helping people stay safe and healthy and partnering for impact. To learn more visit www.syngenta.com and www.goodgrowthplan.com. Follow us on Twitter at www.twitter.com/Syngenta.

Company details

Company typeLarge
IndustryAgricultural Tech & Precision Agriculture
Company size10001

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

Company Description

About Syngenta 

At Syngenta Seeds Field Crops, we're shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We’re a global Ag Tech powerhouse, headquartered in the United States, with passionate, local experts collaborating with farmers to deliver solutions that create market opportunities.  We unite precision breeding, advanced biotechnology trait choice, and digital platforms for unmatched in-field performance.  Our seeds help mitigate risks such as disease, insect, weed, and extreme weather pressures, all while promoting sustainable farming practices that protect and enhance our planet. Join our mission of revolutionizing food security and transforming agriculture. 

Job 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, and 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

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.

  • 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

Desired Qualifications: 

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

Additional Information

What We Offer: 

  • 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. 

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. 

#LI-Remote

WL: 4A

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
Unlocked after you apply
·

Data Scientist Related jobs

Other jobs at Syngenta

Premium

Reach out to the hiring manager directly.

Gain access to the contact details of the hiring managers who actually decide, and reach out to network with them directly. That, plus more when you upgrade:

  • Full match report with fit score and gaps
  • Career diagnostics on how recruiters read you
  • Curated company matches and warm intros
  • 48h early access to new roles

Cancel anytime.