At a Glance
- Tasks: Lead the development of advanced forecasting models to optimise logistics operations.
- Company: Join Relay, a fast-growing logistics startup backed by major investors.
- Benefits: Generous equity, private health coverage, 25 days holiday, and flexible work options.
- Other info: Dynamic team culture focused on innovation and collaboration.
- Why this job: Make a real impact on how goods move in the online world.
- Qualifications: 8+ years in data science with strong Python and SQL skills.
The predicted salary is between 63000 - 77000 £ per year.
Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M), 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
About the role:
Relay's network runs on forecasts. Every shift released in sortation, every middle-mile van dispatched, every last-mile route planned, every expansion decision made - all downstream of models that predict how parcels move through our system. When those models are right, the network runs efficiently and cost per parcel drops. When they drift, the cost compounds across every stage of the operation. The Network squad builds and maintains the forecasting engine that powers all of it, and Demand Forecasting is its core: one forecast of what will be available to sort, at outcode granularity, from D0 out to D30.
What You'll Do:
- Own the integrated forecast end to end. Blend live tracking signals in the near term with model-generated parcels further out into a single view, by area, from today to thirty days ahead.
- Build the hardest models in the area. The model-generated long-horizon forecast, the inbound-international volume forecast, and the parcel size and weight models that make the forecast a measure of physical volume rather than just a count.
- Set the methodology and validation standards for Demand Forecasting. Define how models are evaluated, how accuracy is measured at each horizon, and what 'good' looks like across the area's models.
- Raise the technical bar. Review approaches, make the model-choice and build-vs-buy calls, and mentor the Senior Data Scientist and Analyst alongside you.
- Define the forecast's interfaces. Decide what Demand Forecasting hands to the demand-management layer, to Routing, and to the network-planning function.
- Learn the operational processes your models serve, supported by the squad and the teams who use the forecasts, and identify where the current approach falls short.
- Own production quality across the estate, working with the ML Engineer so that models are monitored, drift is caught early, and accuracy problems are traced to the right cause.
- Work with Finance, who extend the operational forecasts into longer-range financial projections.
- Quantify the impact of model error on cost per parcel, and use it to decide where the area invests effort.
Who Will Thrive in This Role?
- You have been the technical anchor on a modelling team before.
- You think in interconnected systems.
- A deep track record of building and delivering models from ambiguous starting points.
- Strong Python and SQL, and depth across the full modelling lifecycle.
- At least 8 years in a data science or quantitative modelling role.
- You communicate with non-technical stakeholders with authority.
- You're comfortable using AI tools to accelerate your workflow.
- This role suits someone who wants to see whether their models made a real difference to how the network operates.
- Logistics or delivery network experience is a plus.
Compensation, Benefits & Workplace:
- Generous equity, richer than 99% of European startups.
- Private health & dental coverage.
- 25 days of holidays.
- Enhanced parental leave.
- Located in Shoreditch, our office set-up enables in-person interactions.
- We work 4 days on-site, with 1 day remote.
- 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.
- All In, All the Time: You show up and step up.
- People-Powered Greatness: You invest in your teammates.
- Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers.
Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Staff Data Scientist - Network employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
