Senior Data Analyst - Strategic Finance

Relay Technologies
City of London
3 weeks ago
Create job alert

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 (whose portfolio spans fusion energy and space exploration), 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
~90 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, are made by a finance team that runs on data: driver‑level metrics, profitability models, pricing structures, and operational KPIs. This role exists to own the analytics layer that powers those decisions.


As a Senior Data Analyst in the finance squad, you are responsible for how finance sees the business. You own the dashboards and reporting that give visibility into the metrics that matter: cost per parcel, expansion profitability, client and cohort performance, pricing dynamics, and the drivers underneath them. You translate raw operational data into views that finance can use to forecast, model, and act.


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 finance squad, but report into the centralised data team. You will work closely with the Senior Data Scientist in the squad, building the reporting and visibility layer on top of their simulation models. You will also work across squads, pulling the metrics they commit to the semantic layer and shaping them into the views finance needs.


Who Will Thrive in This Role?



  • You take ownership of your domain. You don't wait to be told what finance needs or when something is broken. You're proactive about understanding the questions they're trying to answer and making sure the data is there to answer them.


  • You're an excellent data analyst who builds clean, reliable reporting that people actually use. You care about data quality, clarity, and making complex metrics understandable.


  • You're fluent in SQL and experienced with dbt. You can build and maintain well‑structured models, not just write queries.


  • You're comfortable with BI tools and visualisation platforms. You know how to design dashboards that surface the right information without clutter.


  • You have at least 5 years of experience, ideally with some exposure to finance, FP&A, or commercial analytics. You understand how finance teams think about metrics and drivers.


  • You communicate clearly with non‑technical partners. Finance will rely on your reporting to make decisions. You need to explain what it shows, where the data comes from, and where the limitations are.


  • You're comfortable working across teams. You'll pull metrics from squads across the business, which means building relationships and understanding how different parts of Relay operate.



Fast and Focused Hiring Process

  1. Talent Acquisition Interview - 30 min


  2. Technical SQL Interview - 1 hours


  3. Hiring Manager Interview - 45 min


  4. Case Study - 1 hour


  5. Values & Impact Interview - 45 min


  6. Decision and offer within 48 hours. Our process mirrors our pace of work.



Compensation, Benefits & Workplace



  • 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.


  • Located in Shoreditch, our office set‑up enables the kind of in‑person interactions that drive impact. 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. 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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.