Operation research engineer
Listed on 2026-06-21
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Engineering
AI Engineer (Applied/Software), Data Science Manager -
IT/Tech
AI Engineer (Applied/Software), Data Scientist, Data Science Manager, Machine Learning/ ML Engineer
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.
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's Analytics & Data Sciences Team is seeking an Operations Research Engineer in Malta, IL. This role will drive operational efficiency and decision quality across Seeds Research & Development by designing, building, and scaling algorithmic decision-support solutions.
The role applies Operations Research and Mathematical Optimization to complex end-to-end business processes—translating business objectives and constraints into robust models, integrating them into Syngenta's digital ecosystem, and enabling measurable improvements in service, cost, speed, and resource utilization.
Accountabilities:
- Design, build, and deploy mathematical optimization models using Linear Programming (LP), Mixed-Integer Programming (MIP), Nonlinear Programming (NLP), Constraint Programming (CP), and hybrid approaches as appropriate.
- Translate business objectives, constraints, and operating policies into robust mathematical formulations with clear assumptions and acceptance criteria.
- Integrate optimization solutions into Syngenta's digital ecosystem.
- Identify, collect, cleanse, and structure data from multiple sources; define input/output specifications, data quality requirements, and data lineage for optimization models.
- Define and align business KPIs and metrics that drive optimization objectives and enable value tracking.
- Validate models through testing, back-testing, and scenario analysis; run simulations and what-if analyses to assess robustness and quantify trade-offs.
- Lead and manage projects delivering optimization solutions for strategic decisions and day-to-day operations,
such as scope, timeline, risks, and stakeholder alignment. - Collaborate with cross-functional teams and line-of-business users to review current operational systems and processes, identify pain points, and prioritize optimization use cases.
- Communicate clearly on bottlenecks, insights, and recommendations to enable informed decisions by management and operational teams.
- Work in an agile way and adhere to engineering best practices.
- Contribute to capability building by developing technical training materials and curricula to support adoption and awareness of Operations Research solutions.
- PhD in Operations Research, Applied Mathematics, Industrial Engineering, Data Science, Management Science, Computer Science, or a related field.
- 5+ years of applied experience designing, building, and deploying Operations Research / Mathematical Optimization solutions in an industrial context.
- Strong understanding of Operations Research techniques with emphasis on mathematical programming.
- Proficiency in Python for optimization, data processing, and automation; ability to write production-quality, maintainable code.
- Hands-on experience with optimization solvers and modeling tools (e.g., Gurobi, SCIP, FICO Xpress, COPT) and building end-to-end optimization applications.
- Strong problem-framing and structured problem-solving skills: ability to identify complex business problems, assess fit for OR techniques, and deliver scalable decision-support solutions.
- Proven track record delivering implemented business process improvement solutions with measurable impact.
- Ability to identify, access, and translate…
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