At a Glance
- Tasks: Analyse data to optimise parcel routing and sortation for efficient delivery.
- Company: Fast-growing logistics startup backed by major investors, reshaping e-commerce delivery.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Join a dynamic team making online shopping seamless and accessible for everyone.
- Qualifications: Strong analytical skills and experience with data analysis tools.
The predicted salary is between 39600 - 48400 £ 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
Overview
Relay is a parcel delivery network. Every night, parcels from online retailers arrive at our sort centres, are sorted into delivery routes, and go out the next day with couriers. Two things have to go right for that to work. Routing is the planning side: software that decides, before parcels have even arrived, which ones to expect, how to group them into routes, and how to make those routes efficient for couriers to drive. Sortation is the physical side: warehouse teams and sorting robots turning a building full of parcels into neatly separated routes, thousands of times a night. The two are tightly coupled. If the plan expects a parcel that never arrives, a courier's route has a hole in it. If the warehouse sorts a parcel the plan didn't expect, it has nowhere to go.
Relay operates a centralised data team of around 30 data engineers, analysts, and data scientists, with analysts embedded into teams across the business. You will sit with the Routing & Sortation teams but report into the central data team, working daily with software engineers, warehouse operations, commercial, and finance.
What You'll Do
Routing
- Monitor the health of each night's route plans: how many parcels each route carries (planned vs what actually happened), how far couriers travel before their first delivery, and the routes no courier should ever be handed.
- Track how well we predict which parcels will arrive each night: when expected parcels don't show up, or unexpected ones do, work out whether the cause was the retailer's data, a warehouse error, or timing, and improve the prediction rules client by client.
- Act on what you find: flag issues to warehouse managers and retailer-facing teams, and correct the plan when a retailer's parcels arrive outside the normal flow.
- Monitor the route optimisation engine itself and flag regressions when the software or its inputs change.
- Quantify how route design affects courier productivity: deliveries per hour, stops per route, distance between drops - and how far our actual routes sit from the best theoretically possible.
- Build the reporting that diagnoses the middle leg of the network: the van journeys that move sorted parcels from sort centres out to local pick-up points where couriers collect them.
- Partner with the engineers who build the routing systems to test and validate changes.
Sortation
- Investigate cost per parcel: where are we spending too much, where are savings available, and what's driving the variance.
- Track warehouse operative performance: throughput, accuracy, shift utilisation, and the balance between permanent and agency labour.
- Monitor sorting robot efficiency and capacity: what volumes can they sustain, where are the bottlenecks, how do they compare to manual sorting.
- Build models to predict how many operatives each shift needs, and help automate workforce planning around the best performers.
- Compare the parcel volumes retailers actually send us against what they told us to expect, and find where the gaps come from.
- Define KPIs and build dashboards that make routing and sortation performance transparent to operations.
Data Analyst - Routing & Sortation in London employer: Relay
Relay is an exceptional employer, offering a dynamic and intellectually vibrant work culture that fosters first-principles thinking and relentless experimentation. As a Data Analyst in Routing & Sortation, you will be part of a talent-dense team dedicated to reshaping logistics, with ample opportunities for professional growth and collaboration across engineering, operations, and commercial teams. Located in a fast-paced environment backed by significant investment, Relay provides a unique chance to contribute to a mission that aims to make online commerce more accessible and efficient for everyone.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Routing & Sortation in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Analyst - Routing & Sortation in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Relay. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Relay
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Relay!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.