Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist - Payments

Cleo AI
City of London
5 days ago
Create job alert
Job Responsibilities
  • Improving our current machine learning models and deploying into production
  • Actively building and productionising classifiers - no dependencies on engineering teams
  • Collaborating with various departments within the organisation, including product, operations, and commercial, to leverage machine learning and analytics in order to uncover opportunities for optimization
  • Carrying out deep analysis into the core aspects of how Cleo runs to be able to fully understand the levers and propose opportunities to improve
  • Working closely with engineers to make sure we collect the right data to produce relevant business insights
About you
  • At least 5 years of experience in data science, ML engineering or related roles
  • Ability to write production quality code in Python and SQL
  • Experience deploying machine learning models into production
  • Track record in payments, pricing, or other business process optimisation problems
  • Comfortable with complexity & developing a holistic understanding of a system in order to propose & build solutions
  • A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner
Nice to have
  • Experience with the US payments ecosystem
  • Experience with containers and container orchestration: Kubernetes, Docker, and / or Mesos, including lifecycle management of containers
What do you get for all your hard work?
  • Salary banding can be seen here. You'll also have equity options. You can view our progression framework and salary bandings here : https : / / cleo-ai.progressionapp.com / - This role would be from level DS4 depending on experience
  • Work at one of the fastest growing tech startups, backed by top VC firms, Balderton & EQT Ventures.
  • Cleo is a culture of stepping up. We want, and expect you to grow and develop. That means trying new things, leading others, challenging the status quo and owning your impact. You’ll have our support in everything you do. But more importantly, you’ll have our trust.
  • We treat you as humans first, employees second. Because we can’t fight for the world’s financial health, if we’re not healthy ourselves. This means the usual perks but it also means flexibility.
  • Other benefits include;
  • 25 days Annual leave a year + public holidays (+an extra day for every year you spend at Cleo)
  • Regular lunch-and-learns as part of a general learning culture
  • Online courses and internal training to level up your skills like from coding, to SQL, to management training
  • Choose your own gear, ask for the tools you need, and we’ll seek them out for you
  • Cleo socials and activities
  • Online mental health support via Spill
  • We'll pay for your OpenAI subscription
  • A clear career progression path through Progression https : / / cleo-ai.progressionapp.com /
  • And many more!

UK App access: The Cleo app is no longer downloadable in the UK (but only until next year). If you’re an existing user, you’ll still have access to the app. But some features won’t be available (just for a little while). Why? 99% of our users are based in the US – where financial health is often overlooked. We’ve decided to shift our focus to where we can provide the most value and make the greatest impact for users who need it most. Then we’ll be able to apply what we learn to better support our UK users in the future. Check out this page for more information.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.