Senior Data Scientist - Operational Research
London, Greater London, United Kingdom
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou will work alongside Data Scientists, Analysts, and Engineers in a squad focussed on developing the tech defining our last mile marketplace.
Translate operational requirements into optimisation models across scheduling, assignment and pricing problems.
Work closely with engineering to productionise your solutions into automated daily processes
From the employer’s posting
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.
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.
Tools in this posting
- Julia
- Python
- Rust
- C++
Source — Tool mentions in context
- 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
- Hiring Manager Interview - 45mins - Python Live Coding - 60mins - Case Study - 60mins
Benefits in the posting
Full benefits wording- Private health & dental coverage, so comprehensive you’d need to be a partner at a Magic Circle law firm to match it.
- Enhanced parental leave.
From the employer’s posting.
Job description
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, and a recently closed Series B ($95M), Relay is scaling faster than 99% 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
• ~160 people, around 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
Talent Acquisition Interview - 30mins | Online
Hiring Manager Interview - 45mins
Python Live Coding - 60mins
Case Study - 60mins
Relay Operating Principles & Impact- 60mins
Decision and offer within 48 hours. Our process mirrors our pace of work.
Compensation & Benefits
Generous equity, richer than 99% of European startups, with annual top-ups to share Relay’s success.
Private health & dental coverage, so comprehensive you’d need to be a partner at a Magic Circle law firm to match it.
25 days of holidays
Enhanced parental leave.
Hardware of your choice.
Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more).
Who Thrives at Relay?
Aim with Precision: You define problems clearly and measure your impact meticulously.
Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience.
All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts.
People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success.
Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we.
If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let’s connect.
Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
London, Greater London, United Kingdom
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 26, 2026
- Recorded sightings
- 85
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Jun 24, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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