Coupa
Principal Operations Research Scientist
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
26 September 2026
What they need
Job Summary
Coupa makes margins multiply through its community-generated AI and industry-leading total spend management platform for businesses large and small. Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers. We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins.
Responsibilities
- Algorithmic Leadership: Take end-to-end technical ownership of complex optimization features. Formulate, prototype, and implement advanced mathematical models (MIP, LP, NLP, Network Flow, and custom heuristics) to solve strategic sourcing and supply chain challenges.
- Architecture Scalability: Partner with software architects to integrate optimization models into Coupa s high-throughput, multi-tenant SaaS platform. Ensure the code is modular, well-tested, and built to handle massive enterprise datasets.
- Solver Tuning Optimization: Bench-test, profile, and tune commercial solvers (eg , Gurobi, CPLEX, Google OR-Tools) to dramatically improve performance, solve times, and memory footprint under strict application SLAs.
- Technical Mentorship: Act as a force multiplier by mentoring senior and junior engineers/scientists. Establish code review standards and run design sessions to elevate the teams mathematical and engineering practices.
- Cross-Functional Collaboration: Work closely with Product Managers and Senior Engineering leaders to define feature requirements, translate business objectives into technical specifications, and manage algorithmic trade-offs.
- Empirical Validation: Design robust validation frameworks and simulation environments to thoroughly test model behavior, ensuring stability and mathematical correctness against highly variable, messy real-world data.
What You Will Bring to Coupa
- Master s degree or Ph. D. in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a closely related field.
- 12+ years of industry experience applying operations research methods and deploying production-level optimization models in commercial environments at scale.
- Expert knowledge of mathematical programming and deep experience with authoring model formulations for commercial solvers (such as Gurobi, CPLEX, or Xpress).
- Strong programming proficiency in Python, Java, C++, C# or Go, with a solid understanding of software design patterns and object-oriented programming.
- Deep understanding of computational complexity, advanced data structures, and algorithmic design.
- Excellent communication skills, with a proven ability to explain highly complex mathematical behaviors to product and business leaders.
- You are an elite mathematical modeler who also loves writing clean, production-grade code.
- You are highly analytical, self-driven, and excel at converting ambiguous, high-level business constraints into structured, elegant algorithms.
- You enjoy mentoring others and are passionate about cultivating a highly collaborative, intellectually rigorous engineering culture.
- You embody Coupa s core values: Ensure Customer Success, Focus on Results, and Strive for Excellence.
What Will Give You a Competitive Edge (Preferred Qualifications)
- Deep domain expertise in Supply Chain Network Design, Inventory Optimization, Production/Scheduling Optimization, Routing Optimization, Strategic Procurement, and/or Logistics.
- Experience utilizing Machine Learning techniques (eg, forecasting, clustering) in tandem with mathematical optimization models.
- Experience with PySpark, SQL, and processing large-scale datasets in distributed computing environments.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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