Senior Data Scientist - Network Simulation in London

Senior Data Scientist - Network Simulation in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Relay Technologies

At a Glance

  • Tasks: Join us to evolve our digital twin and build strategic models that drive decisions.
  • Company: Relay, a fast-scaling logistics startup backed by major investors.
  • Benefits: Generous equity, private health coverage, 25 days holiday, and extensive perks.
  • Other info: Dynamic team culture focused on innovation, collaboration, and continuous improvement.
  • Why this job: Make a real impact in reshaping e-commerce logistics with cutting-edge technology.
  • Qualifications: Strong modelling skills, Python and SQL proficiency, and experience in financial modelling.

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 is scaling fast. The decisions that shape that growth - where to expand, how to price, where to invest - rest on models that simulate how the network behaves and how it evolves as density, geography, and operating models change. We have an MVP tool for this today; we need someone to help productionise it and build the next generation of strategic models on top of it.

You'll be a core contributor to Relay's digital twin - a network simulator that captures our unit economics end-to-end, from first-mile collection through sortation, middle-mile and last-mile. It's already in use by finance, but it's a living system: every operating-model change, new service type, or commercial scenario means upgrading a component, adding a model, or building a new view. Your job is to help keep it accurate and to extend it where the business asks new questions.

Your remit splits roughly equally between two halves:

  1. Evolving the digital twin. You understand each cost component deeply, you help identify where the current models are wrong or incomplete, and you upgrade them systematically. When a new first-mile operating model is rolled out, you upgrade that engine. When a new service type changes sortation cost, you understand it at a granular level and model it properly. You add new flows, surface new metrics, and harden the parts that matter most for the decisions being made.
  2. Building new strategic models and forecasts. Volume forecasts, predictive models, new scenario tooling - work that sits inside or alongside the twin. You help decide what should live in the twin and what should stand alone. You pick the right tool for the question - classical statistical modelling, financial modelling, simulation, or ML where it earns its place.

Your primary partner is the finance team - Strategic Finance, Commercial Finance, FP&A. You translate their questions into modelling problems and give them tools that let them explore pricing, margin and projection scenarios dynamically rather than waiting for analysis to be rebuilt manually. You contribute to the roadmap - taking in their needs, helping prioritise what to build, and shipping it.

You're part of a data org of around 30 engineers, analysts, and data scientists, but embedded in the finance squad. A dedicated finance analyst within the squad partners with you directly - they build the reporting and visibility layer on top of your models and feed prioritisation back to you. You'll work alongside more senior data scientists who own the broader direction of the twin.

Who will thrive in this role

  • You're a strong modeller who thinks in systems. You naturally break complex problems into components, understand the assumptions behind each one, and know when those assumptions need revisiting.
  • You're a builder. You don't wait for requirements to be handed to you. You go and understand the problem, figure out what's needed, and ship something useful. Then you iterate.
  • You're fluent in Python and SQL, and comfortable doing your own data engineering. You can pull, transform, and model data without needing someone else to prepare it for you.
  • You bring strong software engineering principles into your modelling work. The digital twin is a real production system - Python, SQL, APIs, a frontend - and you'll work across that stack. You don't need to be a frontend specialist, but you should be at ease in a production codebase: writing tested, readable code, designing modular components, shipping changes that someone else can pick up next week.
  • You have experience with financial modelling, forecasting, or simulation, ideally in a context where your models informed commercial or strategic decisions - not just produced analysis. You know your way around ML and use it where it materially improves accuracy.
  • You communicate clearly with non-technical partners. Finance will rely on your models to make decisions. You need to explain what they do, where they're reliable, and where they're not.
  • You care about the problem more than the technique. You'll use whatever modelling approach fits. The point is accuracy, speed, and usefulness - not methodological elegance.
  • You take ownership of your work. You manage trade-offs and hold yourself accountable for whether the models are actually driving better decisions.
  • Logistics or delivery network experience is a plus, but what matters more is the ability to learn a complex operational domain quickly and model it well.

Compensation and 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.

Senior Data Scientist - Network Simulation in London employer: Relay Technologies

Relay is an exceptional employer, offering a vibrant work culture that thrives on innovation and collaboration. With generous equity options, comprehensive health benefits, and a commitment to employee growth through continuous learning and feedback, Relay empowers its team to tackle complex challenges in the logistics industry. Located in a dynamic environment, employees enjoy extensive perks and a supportive atmosphere that fosters both personal and professional development.

Relay Technologies

Contact Details:

Relay Technologies Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Scientist - Network Simulation in London

Tip Number 1

Network, network, network! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at Relay or in logistics. You never know who might have the inside scoop on job openings!

Tip Number 2

Show off your skills! If you’ve got a portfolio of projects or models you’ve built, don’t be shy about sharing them. Create a GitHub repo or a personal website to showcase your work. This gives potential employers a taste of what you can do and how you think.

Tip Number 3

Prepare for interviews like it’s game day! Research Relay’s mission and values, and think about how your experience aligns with their goals. Be ready to discuss specific examples of how you’ve tackled complex problems and contributed to team success.

Tip Number 4

Don’t forget to 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. Let’s make it happen!

We think you need these skills to ace Senior Data Scientist - Network Simulation in London

Python
SQL
Data Engineering
Financial Modelling
Forecasting
Simulation
Machine Learning

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with modelling, Python, and SQL, and don’t forget to showcase any relevant projects that demonstrate your ability to build and iterate on complex systems.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about Relay’s mission and how your skills align with the role. Be specific about your experience in financial modelling and how it can contribute to the team.

Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems in the past. Relay values builders who take ownership, so share instances where you identified issues and implemented solutions independently.

Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!

How to prepare for a job interview at Relay Technologies

Know Your Models Inside Out

Before the interview, dive deep into your modelling experience. Be ready to discuss specific models you've built, the assumptions behind them, and how they informed strategic decisions. Relay values a strong understanding of complex systems, so showcasing your ability to break down problems will impress.

Showcase Your Coding Skills

Brush up on your Python and SQL skills. Prepare to demonstrate your coding abilities, perhaps through a live coding exercise or by discussing past projects. Highlight how you’ve applied software engineering principles in your modelling work, as this is crucial for the role.

Communicate Clearly with Non-Technical Partners

Practice explaining your models and their implications in simple terms. Relay's finance team will rely on your insights, so being able to convey complex ideas clearly is key. Think of examples where you successfully communicated technical concepts to non-technical stakeholders.

Emphasise Your Ownership and Iteration Mindset

Relay is looking for builders who take ownership of their work. Be prepared to share examples of how you've identified problems, taken initiative, and iterated on solutions. Highlight your commitment to continuous improvement and how it has led to better outcomes in your previous roles.