At a Glance
- Tasks: Monitor and enhance forecasting models to ensure operational efficiency.
- Company: Join Relay, a fast-growing logistics startup backed by major investors.
- Benefits: Competitive salary, inclusive culture, and opportunities for career growth.
- Other info: Dynamic team environment focused on innovation and collaboration.
- Why this job: Make a real impact on e-commerce by optimising delivery forecasts.
- Qualifications: 5+ years as a data analyst, fluent in SQL, and strong analytical skills.
The predicted salary is between 60000 - 80000 £ 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
The Opportunity
Relay's network runs on forecasts. How many parcels arrive tomorrow? Which ones to sort tonight? How many shifts to release? When those forecasts are wrong, the cost shows up in CPP: too few shifts and you pay surge premiums, too many and you waste capacity. Behind each forecast is a model, and those models need someone watching them, catching drift, and surfacing problems before they hit operations.
As Lead Data Analyst for the Network squad, you will own the analytical oversight across Relay's forecasting systems. That means tracking model performance across demand forecasting, shift planning, dimensions, and BPP inclusion. When a model starts missing, you catch it. When forecast error costs money, you quantify it. When stakeholders say 'the forecast was wrong,' you investigate and build the case for what to fix.
This is not a model-building role. The Network squad's Data Scientists build and ship the forecasting models. Your job is to ensure those models keep working, to set analytical standards for the squad, and to be the first line of defence when something breaks. You will work closely with Sortation, Middle Mile, Last Mile, Routing, and Finance to understand where forecasts are working and where they're not.
Relay operates a centralised data team of around 30 data engineers, analysts, and data scientists, with analysts embedded into squads across the business. You will sit in the Network squad, reporting to the Squad Lead. Depending on your experience, this role also offers line management opportunities.
What You'll Do
- Track forecast accuracy across all Network models: demand forecasts, shift planning forecasts, dimensions model, BPP inclusion models
- Surface model drift and performance issues before they impact operations - you're the early warning system
- Diagnose forecast errors by client, geography, day of week, and horizon, and quantify the CPP impact
- Build dashboards that make model performance transparent to the squad and stakeholders
- Set analytical direction for the Network squad: define what metrics matter, where to invest analytical effort
- Work with Data Scientists to build the business case for model improvements, whether that's new input signals, data quality fixes, or client-specific treatment
- Monitor how capacity matches demand across Sortation, Middle Mile, Last Mile, and track shift release effectiveness
- Translate model performance into business impact that stakeholders can act on
Who Will Thrive in This Role?
- You catch problems before they become crises - you're vigilant about when models start behaving unexpectedly
- You're obsessive about data quality and forecast accuracy - you hold models accountable for their predictions
- You're fluent in SQL and experienced with dbt/BigQuery - you can build and maintain analytical models
- You've built dashboards that are operationally critical, not just 'nice to have'
- You have a passion for forecasting and predictive modelling - you're energised by understanding where predictions hit and where they miss
- You translate technical performance into business impact - CPP, surge costs, wasted capacity
- You're comfortable challenging Data Scientists when models aren't performing, and working with them to improve
- You communicate clearly with operations teams and can explain what the data shows without the jargon
- You have at least 5 years of experience as a data analyst or similar role
- You care about impact more than insight - you measure success by whether forecasts drive better decisions
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.
Lead Data Analyst - Network in London employer: Relay Technologies
Relay is an exceptional employer, offering a vibrant work culture that thrives on innovation and collaboration. With a focus on employee growth, the company provides opportunities for advancement within a dynamic team of experts in data and engineering, all while being backed by significant investment to drive its mission of transforming logistics. Located in a fast-paced environment, Relay encourages a culture of continuous improvement and values each team member's contributions, making it an ideal place for those seeking meaningful and impactful work.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Analyst - Network in London
✨Tip Number 1
Network like a pro! Attend industry events, webinars, or meetups related to data analytics and logistics. You never know who you might bump into that could help you land that Lead Data Analyst role at Relay.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your analytical projects, especially those involving forecasting and model performance. This will give you an edge when discussing your experience with potential employers.
✨Tip Number 3
Don’t be shy about reaching out! Connect with current employees at Relay on LinkedIn. Ask them about their experiences and express your interest in the Lead Data Analyst position. A personal touch can go a long way!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Relay team.
We think you need these skills to ace Lead Data Analyst - Network in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Lead Data Analyst role. Highlight your experience with forecasting, data quality, and model performance, as these are key aspects of the job. We want to see how your skills align with our mission at Relay!
Showcase Your Analytical Skills:In your application, don’t just list your skills; demonstrate them! Use specific examples where you've tracked model performance or diagnosed forecast errors. This will help us see your analytical mindset in action and how you can contribute to our team.
Be Clear and Concise:When writing your application, keep it straightforward. Avoid jargon and make sure your points are easy to understand. We appreciate clarity, especially when it comes to communicating complex data insights!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Relay!
How to prepare for a job interview at Relay Technologies
✨Know Your Forecasts
Before the interview, brush up on your understanding of forecasting models and their importance in logistics. Be ready to discuss how you would track forecast accuracy and surface model drift, as this role hinges on your ability to ensure models are performing optimally.
✨Showcase Your Analytical Skills
Prepare examples that highlight your experience with SQL and analytical tools like dbt or BigQuery. Relay is looking for someone who can build and maintain critical dashboards, so be ready to share specific instances where your analytical skills made a tangible impact.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You’ll need to communicate effectively with operations teams, so think about how you can convey technical performance and its business implications without jargon. This will demonstrate your ability to bridge the gap between data and operations.
✨Emphasise Team Collaboration
Relay values teamwork, so come prepared to discuss how you've worked with data scientists and other stakeholders in the past. Highlight your experience in giving and receiving feedback, and how you’ve contributed to building trust within a team. This will show that you’re not just a lone wolf but a team player.