Senior Operational Research Scientist - Last Mile

Relay Technologies
London - HybridPosted 22 April 2026

Job Description

Senior Operational Research Scientist - Last Mile Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay’s Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. THE TEAM • ~110 people, more than half in engineering, product and data • 45+ advanced degrees across computer science, mathematics and operations research • Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle • An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation The Opportunity A last-mile marketplace runs on decisions — which parcels? on which routes? delivered by which couriers? at what price? Thousands of them, made every single day. Good decisions have fast and meaningful impact across the entire Relay Network. Our Operational Research team are responsible for the intelligent systems that optimise the most complex decisions across our network. As the first Operational Research Scientist in Last Mile Marketplace, you will design, build and evolve the optimisation models and solvers that sit at the heart of Relay's last-mile network — These are production Decision systems that shape how Relay operates every day. This is a senior individual contributor role. You will work alongside Data Scientists, Analysts, and Engineers in a squad focussed on developing the tech defining our last mile marketplace. This role sits within Relay’s Data function, joining a dedicated Operational Research team, reporting into the Staff Decision Systems Architect. What You'll Do - Translate operational requirements into optimisation models across scheduling, assignment and pricing problems. - Develop and evaluate solution approaches — drawing on knowledge of mathematical programming and meta-heuristics. - Design and build algorithms, heuristics and solvers bespoke for the unique problems you formulate. - Ensure your solutions are scalable and adaptable to our growing operation. - Benchmark and evaluate the performance of your solutions - Work closely with engineering to productionise your solutions into automated daily processes - Work with analytics to monitor the daily performance of your solution, using this information to proactively evolve your solution to make better decisions. Who Will Thrive in This Role? - You want to be close to the problems you are optimising, and decisions your solutions will make, getting hands-on in the network to see the outcome of your work first hand. - You have relevant operational research experience in heuristics and/or mathematical programming. - You are comfortable coding in a general purpose or performance language, such as Python, Rust, Julia or C++ - You enjoy the challenge of solving large-scale optimisation problems - You are motivated to work on production systems, learning from the realised outcome of your optimisation model every day, and proactively evolving your solution. - You love understanding problems deeply, crafting bespoke solutions to unique dynamics of the decision being made. - You are excited to work in a cross-functional tech team designing and building Relay’s Last Mile Marketplace - You care about the people your work affects — couriers, retailers, and consumers all feel the decisions these systems make Fast and Focused Hiring Process 1. Talent Acquisition Interview - 30mins | Online 2. Hiring Manager Inter ... (truncated, view full listing at source)
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