OR Scientist

Job description

**About the Company** **Why We Built Lyric:** Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions that could impact the bottom line. Powerful algorithms and AI can address these problems, yet most organizations struggle to leverage supply chain AI at scale. The current SCM technologies are either rigid, limited-scope point solutions or custom solutions built in-house, which demand immense expertise and investment. That is…until now. **Enter Lyric**: Lyric is an enterprise AI platform built specifically for supply chains, offering the best of both worlds: - **Out-of-the-box AI solutions** for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more, ***plus*** - **A platform-first approach** that empowers both business and technical users with end-to-end product composability, leveraging no-code tools, their own code, or even forking our code to build and refine supply chain decision intelligence With Lyric, enterprises no longer have to choose between flexibility and speed, they get both. **The Mission:** We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like Lyric. Since our inception in December 2021, that conviction has been validated time and time again. Today, a growing number of Fortune 500 companies, including Smurfit WestRock, Estée Lauder, Coca-Cola, and more, are innovating on their own terms with Lyric. We can’t wait to see what our customers, both current and future, are empowered to build with us next. Come build with us! **LYRIC** *Decision Science* **OR Scientist / Algorithms Engineer** Full-time · Decision Science team · Reports into Algorithms/Applied Science leadership **About Lyric** Lyric builds an AI-native platform for supply chain decisions, where modeling, planning, and applied decision science run on a single composable architecture. The platform gives enterprise supply chain teams out-of-the-box algorithms for network optimization, inventory allocation, routing, fulfillment capacity planning, order promising, demand propagation, and scenario analysis — alongside a platform-first layer that lets business and technical users build and extend that intelligence with no-code tools or their own code. Lyric is backed by leading enterprise software investors and works with global Fortune 500 supply chain organizations. The team is built around deep, applied expertise at the intersection of operations research, algorithms, and supply chain — and the OR Scientist / Algorithms Engineer ladder is the technical core of that team. **About the Role** As an OR Scientist / Algorithms Engineer, you'll turn ambiguous, messy supply chain problems — inventory, network design, routing, planning, capacity — into correct, well-reasoned optimization models, and ship them as production-grade software. You'll work across the full arc from problem formulation through solver implementation to communicating impact, and you'll use (and help shape how the team uses) AI/LLM tooling as both a build accelerator and a product building block. This is an entry/early-career IC role on our ladder: you'll own well-scoped pieces of a bigger problem under the guidance of senior scientists, with a clear growth path to Senior, Lead, and Principal as your scope and independence grow. **What You'll Do** - Formulate real supply chain decisions — inventory, routing, network design, planning, capacity — as LP/MIP, network flow, heuristic, or simulation models, stating and defending your assumptions. - Diagnose and improve slow or infeasible optimization models: tighten formulations, apply valid inequalities, warm starts, decomposition, or heuristics as the situation calls for. - Write clean, tested, production-grade Python (or the team's language) against solvers and modeling layers (e.g. Gurobi, CPLEX, OR-Tools via Pyomo/JuMP), and take models from prototype toward reliable, monitored production use. - Use AI/LLM and agentic tooling critically — as an accelerator you validate line-by-line, and, where relevant, as a component you help design, evaluate, and guardrail inside an algorithmic pipeline. - Connect every model back to the business decision it serves — service levels, lead times, plan stability — and recognize when an “optimal” plan is operationally useless. - Explain your formulation, trade-offs, and results clearly to both technical and non-technical audiences, and take feedback as input rather than verdict. **What We're Looking For** **Required** - Hands-on experience formulating and solving real optimization problems — LP/MIP, heuristics, network flows, or simulation — beyond coursework alone. - Professional software engineering practice in Python (or a comparable language): version control, testing, and code review, not just notebooks. - Exposure to at least one commercial or open-source solver via a modeling layer (e.g. Gurobi, CPLEX, OR-Tools, Pyomo, JuMP) — or clear evidence you pick this up fast. - A critical, hands-on posture toward AI/LLM coding tools: comfortable using them, and equally comfortable explaining where they've gone wrong. **Preferred** - Prior exposure to supply chain or a comparable operational-decision domain (inventory, transportation, planning, network design). - A track record of work that ran at real scale — large problem instances, meaningful SKU/location/order volumes, live production traffic — rather than only academic or proof-of-concept work. - Experience shipping something that stayed in production and that others depended on, including monitoring and iteration, not just a handed-off prototype. - A self-initiated project or improvement you drove end-to-end without being asked — we place a lot of weight on this kind of ownership. - A novel formulation, technique, framework, paper, patent, or open-source contribution that measurably beat the prior approach. - Background at a company or lab doing optimization, supply chain, or algorithmic decisioning at scale (logistics, e-commerce, ride-hailing, marketplaces, manufacturing, OR-heavy tech, or a strong research group). **Why Join Lyric** - Work on optimization and algorithms that run in production for large enterprise supply chains, not academic exercises. - Shape how AI/LLM and agentic tooling get used alongside classical OR — as both a build accelerator and a product feature. - Join a team built around deep, applied OR and supply chain expertise, with a clear ladder from OR Scientist through Senior, Lead, and Principal. *Lyric is an equal opportunity employer. We welcome applicants from all backgrounds and experiences.*