Senior Data Scientist

Lendable
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist – Machine Learning -  Defence –Eligible for SC

Senior Data Scientist

Senior Data Scientist - Crypto

Senior Data Scientist - Crypto

Senior Data Scientist London, England

About Lendable

Lendable is on a mission to make consumer finance amazing:faster, cheaper and friendlier.

We're building one of theworld’s leading fintechcompanies and are off to a strong start:

  1. One of the UK’s newest unicornswith a team of just over 400 people
  2. Among thefastest-growingtech companies in the UK
  3. Profitablesince 2017
  4. Backed by top investors includingBalderton CapitalandGoldman Sachs
  5. Lovedby customers with the best reviews in the market (4.9 across 10,000s of reviews onTrustpilot)

So far, we’ve rebuilt theBig Threeconsumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days.

We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets(UK and US)where trillions worth of financial products are held by big banks with dated systems and painful processes.

Join us if you want to

  1. Take ownership across a broad remit.You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1.
  2. Work insmall teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo.
  3. Build thebest technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting.

About the role

Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products.

You will have access to the latest machine learning techniques combined with a rich data repository to deliver best in market risk models.

Our team's objectives

  • The data science team develops proprietary risk models which are core to the company’s success.
  • We work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.
  • We self-serve with all deployment and monitoring, without a separate machine-learning-engineering team.

How you'll impact these objectives

  • Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling is essential to being able to successfully contribute value.
  • Rigorously search for the best models that enhance underwriting quality.
  • Clearly communicate results to stakeholders through verbal and written communication.
  • Share ideas with the wider team, learn from and contribute to the body of knowledge.

What we're looking for

  • Experience using Python.
  • Knowledge of the credit industry, including the products, data, typical ML applications.
  • Knowledge of machine learning techniques and their respective pros and cons.
  • Confident communicator and contributes effectively within a team environment.
  • Self-driven and willing to lead on projects / new initiatives.

Nice to have's

  • Interest in machine learning engineering.
  • Strong SQL and interest in data engineering.

We’re not corporate, so we try our best to get things moving as quickly as possible. For this role we’d expect:

  • Initial call with TA.
  • Take home task.
  • Task debrief interview.
  • Case study interview.
  • Final interviews;
  • Meet the team you’ll work with daily.
  • Meet Head of Data Science and Chief Risk Officer.

Life at Lendable

  1. The opportunity to scale up one of theworld’s most successfulfintech companies.
  2. Best-in-classcompensation, including equity.
  3. You can work from homeevery Monday and Fridayif you wish - on the other days we all come together IRL to be together, build and exchange ideas.
  4. Our in-house chefprepares fresh, healthy lunches in the office every Tuesday-Thursday.
  5. We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes toprivate health insurance.
  6. We're anequal opportunity employerand are looking to make Lendable the most inclusive and open workspace in London.

Check out ourblog!

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

AI Jobs for Non‑Technical Professionals: Where Do You Fit In?

Your Seat at the AI Table Artificial Intelligence (AI) has left the lab and entered boardrooms, high‑street banks, hospitals and marketing agencies across the United Kingdom. Yet a stubborn myth lingers: “AI careers are only for coders and PhDs.” If you can’t write TensorFlow, surely you have no place in the conversation—right? Wrong. According to PwC’s UK AI Jobs Barometer 2024, vacancies mentioning AI rose 61 % year‑on‑year, but only 35 % of those adverts required advanced programming skills (pwc.co.uk). The Department for Culture, Media & Sport (DCMS) likewise reports that Britain’s fastest‑growing AI employers are “actively recruiting non‑technical talent to scale responsibly” (gov.uk). Put simply, the nation needs communicators, strategists, ethicists, marketers and project leaders every bit as urgently as it needs machine‑learning engineers. This 2,500‑word guide shows where you fit in—and how to land an AI role without touching a line of Python.

ElevenLabs AI Jobs in 2025: Your Complete UK Guide to Crafting Human‑Level Voice Technology

"Make any voice sound infinitely human." That tagline catapulted ElevenLabs from hack‑day prototype to unicorn‑status voice‑AI platform in under three years. The London‑ and New York‑based start‑up’s text‑to‑speech, dubbing and voice‑cloning APIs now serve publishers, film studios, ed‑tech giants and accessibility apps across 45 languages. After an $80 m Series B round in January 2024—which pushed valuation above $1 bn—ElevenLabs is scaling fast, doubling revenue every quarter and hiring aggressively. If you’re an ML engineer who dreams in spectrograms, an audio‑DSP wizard or a product storyteller who can translate jargon into creative workflows, this guide explains how to land an ElevenLabs AI job in 2025.

AI vs. Data Science vs. Machine Learning Jobs: Which Path Should You Choose?

In recent years, the fields of Artificial Intelligence (AI), Data Science, and Machine Learning (ML) have experienced explosive growth. Spurred by the increase in data availability, advances in computing power, and the demand for intelligent decision-making, organisations of all sizes are investing heavily in these areas. If you’ve been exploring AI jobs on www.artificialintelligencejobs.co.uk, you’ve likely noticed that employers use terms like “AI,” “Data Science,” and “Machine Learning”—often interchangeably. While they are closely related, there are nuanced differences between these fields. Understanding these distinctions is key if you’re trying to decide which path suits you best. This comprehensive guide will help you differentiate among AI, Data Science, and Machine Learning. We will discuss the key skills for each, typical job roles, salary ranges, and provide real-world examples of professionals working in these fields. By the end, you should have a clearer idea of where your strengths and passions might fit, helping you take the next step towards securing your ideal role in the world of data-driven innovation.