Data Scientist

LoanTube
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - New

Data Scientist - Contract - 12 months

Who we are

LoanTube is a leading London-based FinTech and FCA Authorised Broker (FRN #753151), empowering individuals and businesses in the UK to access the right credit products to lead their best financial lives.


Our platform is seamlessly integrated into the UK lending ecosystem, delivering real-time, personalised credit offers tailored to users’ unique needs. Since pioneering transparent loan comparison in 2019, we now process over 100k credit applications every month from individuals and businesses alike.


Financial empowerment is at the heart of our mission – to make credit accessible and work for everyone, while maximising financial literacy.


In 2025, we’re doubling down on our commitment to drive financial inclusion for millions of consumers and small businesses left behind by legacy credit providers. We are doing this by further expanding our suite of seamless fintech products that deliver true financial innovation to those who need it most.


Our culture and values

We are a diverse, globally distributed team of innovators and engineers (spanning India, Brazil, the USA, and beyond) working in an incredibly fast-paced, agile environment. Relentless optimism, grit, and adaptability define our culture. If you thrive on challenges and want to help redefine lending, we’d love to hear from you.


At LoanTube, we believe it’s always day one. We’re proudly bootstrapped and self-sustaining, and we’re bringing our scrappy, all-hands-on-deck ethos into the next phase of our explosive growth.


Our culture is built for self-starters who love solving real-world problems. Every role is product-focused, self-motivated, and business-minded. If you’re not a fan of meetings, enjoy taking ownership, and dream of running a business someday, LoanTube is the place for you.


What makes us tick:

  • Extreme Ownership: We set a strategic roadmap as a team and empower individuals to lead. Your project > your process > your responsibility.
  • Collaborative Alignment: Weekly catch-ups ensure every key area of the business stays connected. No one operates in silos; we run the business together.
  • No Bureaucracy: Forget 1:1s and performance plans. Need to discuss something? Just wheel across the room :)
  • Win Together, Lose Together: Everyone here is an entrepreneur at heart. We focus on solutions, not blame, and move forward as a team to build products that truly serve our customers.
  • Learn by Doing: We love to tinker and figure things out. “I’ve never done this before” is a default Tuesday in the office.


If this sounds like the environment for you, keep reading!


The role

At LoanTube, we process vast amounts of data (1,000+ data points per application). Historically, we’ve adopted an 80/20 approach to leveraging this data across marketing and product. As our dedicated Data Scientist, your mission will be to transform this into a strategic advantage by driving our data efforts to the next level.


Sitting at the heart of the core team, you’ll gain a deep understanding of our business to uncover opportunities where advanced modelling can create the most value. From there, you will own the end-to-end lifecycle of model development – from opportunity sizing to deployment and monitoring – to deliver measurable business impact.


What you’ll do

  • Collaborate with colleagues across business domains to identify opportunities to generate value.
  • Build statistical/ML models that deliver tangible business results at scale.
  • Design and execute experiments/analysis to estimate the impact of potential projects.
  • Develop and maintain key metrics and reports for your initiatives.
  • Collaborate with the engineering team to constantly upgrade our data infrastructure.


Who you are

  • At least a Bachelor’s degree in a quantitative field (e.g., Math, Stats, Physics, or Computer Science) and 2+ years of relevant work experience.
  • Experience creating statistical/ML models to solve business problems (customer segmentation, propensity to buy, credit risk etc). 
  • Proficiency in programming/modeling using Python and advanced querying using SQL.
  • Experience taking models from proofs of concept into production within highly scaled data infrastructure (BigQuery, Databricks, pipelines etc)
  • Business mindset. You’re comfortable linking abstract mathematical concepts to tangible business results.
  • You’re genuinely excited to work with us in the office – five days a week – embracing the energy and collaboration of being together.


Benefits

  • Competitive salary + generous profit-sharing / equity package.
  • 20 paid holidays + a “duvet day” on your birthday + bank holidays.
  • £500 annual Learning and Development budget.
  • 1 week work from anywhere policy.
  • Monthly company team events.
  • Top-tier office environment complemented by a complimentary on-site gym.
  • Prime office location in Hammersmith, with easy access to major Tube lines: Piccadilly, Circle, District, H&C.


Selection process

We’ve been on the other side of the table: companies who waste your time, job offers that don’t materialise, and technical tasks that don’t get reviewed.


So here’s our process:

  1. 30 min intro call with Dima – Growth Lead
  2. 30 min technical screening with Henrique – Product Lead (B2C)
  3. Face-to-Face interview in the office with the Founders and our whole team

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.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.