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

Apply Now

Data Scientist

Capital on Tap
City of London
1 week ago
Create job alert
Overview

We are Capital on Tap. Capital on Tap was founded with the mission to help small business owners and make their lives easier. We provide an all-in-one business credit card & spend management platform that helps business owners save time and money. We serve over 200,000 businesses worldwide with a goal to help 1 million small businesses by 2030.

Why Join Us? We empower you to be innovative and solve complex problems. Take ownership, make an impact, and thrive in our scaling and agile environment. This is a hybrid role, working from our London (Old Street) offices 3 days per week.

What You\'ll Be Doing

Are you a data scientist who loves to see your work make a real-world impact? We\'re looking for someone to join our team and help us figure out the smartest ways to grow our US business. You\'ll own your work from the initial idea through to launch, directly influencing our bottom line and shaping how we operate. If you\'re excited by testing your theories and building things that matter, this could be the perfect fit.

  • Create and launch predictive models that tackle challenges across our customer lifecycle.
  • Dive into complex datasets to identify opportunities and support smarter decision-making.
  • Collaborate with a wide range of stakeholders to ensure seamless implementation of analytical solutions.
  • Translate complex analysis into simple, compelling narratives that align the team.
  • After models go live, monitor performance and iterate to improve them over time.
  • Stay curious by exploring the latest tools and techniques in data science to keep us ahead of the curve.
We\'re Looking For
  • Built machine learning models that have solved real business challenges.
  • Strong with Python and SQL and comfortable working with large, complex datasets.
  • A solid background with numbers from education or professional experience.
  • Proactive self-starter who takes ownership of projects from start to finish.
  • Ability to explain complex data and technical ideas clearly.
  • Thrives in a fast-paced environment; startup or consultancy experience is a plus.
Diversity & Inclusion

We welcome and encourage applications from anyone who shares our commitment to inclusivity. We strive to create a space where authenticity thrives, and everyone can do their best work.

Great Work Deserves Great Perks

Our office culture is relaxed and sociable, with perks including a pool table, arcade machine, beer tap, and dog-friendly offices. Check out our benefits:

  • Private Healthcare including dental and opticians services through Vitality
  • Worldwide travel insurance through Vitality
  • Anniversary Rewards (£250, £500, £750) and a 4-week fully paid sabbatical
  • Salary Sacrifice Pension Scheme up to 7% match
  • Octopus EV Salary Sacrifice Scheme
  • 28 days holiday (plus bank holidays)
  • Annual Learning and Wellbeing Budget
  • Enhanced Parental Leave
  • Cycle to Work Scheme
  • Season Ticket Loan
  • 6 free therapy sessions per year
  • Dog Friendly Offices
  • Free drinks and snacks in our offices

Check out more of our benefits, values and mission here.

Other Info

Check out our \"Top Tips\" for interviewing. Keep updated on new job opportunities by following us on LinkedIn. Email if you have any questions.

Excited to work here? Apply! If you\'d like to progress your career within our fast-growing, profitable fintech, click apply and we will aim to respond within 3 working days (may take up to 5 during busy periods).

Seniority level
  • Entry level
Employment type
  • Full-time
Job function
  • Engineering and Information Technology


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Optimisation)

Data Scientist - Tax & Legal

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.