Operation research engineer

Syngenta Group•Malta, IL

4d•Onsite

About The Position

Syngenta’s Analytics & Data Sciences Team is seeking an Operations Research Engineer in Malta, Illinois. The role supports operational efficiency and decision quality across Seeds Research & Development by designing, building, and scaling algorithmic decision-support solutions. It 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. The engineer will develop and validate optimization solutions, connect them with relevant data and business systems, and work with cross-functional teams and operational users to identify and prioritize use cases. The role also includes managing projects, communicating findings and recommendations, following engineering best practices, and building organizational awareness and adoption of Operations Research solutions.

Requirements

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 or 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, including the ability to write production-quality, maintainable code.
Hands-on experience with optimization solvers and modeling tools such as Gurobi, SCIP, FICO Xpress, or COPT, and building end-to-end optimization applications.
Strong problem-framing and structured problem-solving skills, including identifying complex business problems, assessing suitability for Operations Research techniques, and delivering scalable decision-support solutions.
Proven track record delivering implemented business process improvement solutions with measurable impact.
Ability to identify, access, and translate relevant data into actionable, evidence-based decisions, and ensure data quality, consistency, and traceability across sources.
Strong analytical mindset and ability to communicate complex concepts clearly to technical and non-technical audiences.

Nice To Haves

Experience in Manufacturing, Supply Chain, or Logistics environments.
Knowledge of combinatorial optimization techniques.
Familiarity with modern development practices and tooling, including Git/GitHub, code reviews, and testing.
Experience using AI-assisted coding tools such as GitHub Copilot.
Experience building lightweight decision-support interfaces and visualizations, such as Streamlit or similar, to support user adoption.
Ability to operate effectively in a matrix organization by building partnerships and influencing stakeholders at multiple levels without direct authority.
Ability to generate strategic insights from complex analyses and communicate them clearly to drive measurable improvements in operational efficiency and effectiveness.

Responsibilities

Design, build, and deploy mathematical optimization models using Linear Programming, Mixed-Integer Programming, Nonlinear Programming, Constraint Programming, 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 model input/output specifications, data quality requirements, and data lineage.
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, including scope, timeline, risks, and stakeholder alignment.
Collaborate with cross-functional teams and line-of-business users to review operational systems and processes, identify pain points, and prioritize optimization use cases.
Communicate bottlenecks, insights, and recommendations clearly to support informed decisions by management and operational teams.
Work in an agile way and adhere to engineering best practices.
Develop technical training materials and curricula to support adoption and awareness of Operations Research solutions.