Level

Lendable

Analyst

AI in this role

Develop credit risk models and pricing strategies using machine learning and data science techniques in the UK Loans team.

scikit-learnpythonsql
credit-riskpricingmachine-learninganalytics

About Lendable

Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start:

  • One of the UK’s most exciting unicorns with a team of over 800 people

  • Among the fastest-growing tech companies in the UK

  • Profitable since 2017

  • Backed by top investors including Balderton Capital and Goldman Sachs

  • Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)

So far, we’ve rebuilt the Big Three consumer 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: you are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1

  2. Work in small teams of exceptional people: Lendies are relentlessly resourceful. We challenge the status quo to solve problems and find smarter solutions

  3. Build the best technology in-house: we use new data sources, machine learning and AI to make machines do the heavy lifting

About the team

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

Our team is primarily focused on the pricing domain but we also work on other areas including product and credit. We implement a range of machine learning techniques and analytical tools to continually improve our product offering.

About the role

You will be working in the UK Loans team at Lendable and will work on projects related to pricing, funnel and credit optimisation in collaboration with the credit and product teams.

Join us if you want to

  • Work in a small, high-impact team where you will be mentored to solve complex analytical problems, eventually taking ownership of your own models

  • Be resourceful to solve problems and find smarter solutions than the status quo

  • Work closely with other members of the team that will support developing your technical expertise and domain knowledge

Our team's objectives

  • The pricing team owns the loans funnel analytics and pricing strategy

  • We work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions

How you'll impact those objectives

  • Learn the domain of products that Lendable serves, understanding the data that informs strategy and modelling is essential to being able to successfully contribute value

  • Research and propose improvements to our existing pricing strategies and modelling methodology

  • Work closely with the credit team to align pricing decisions with credit risk and underwriting strategy

  • 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

Key Skills

  • Experience using Python (pandas, numpy, scikit-learn) and SQL

  • Theoretical understanding of core ML techniques and statistical principles

  • Strong numerical and analytical skills, comfortable working with large datasets

  • Confident communicator and contributes effectively within a team environment

  • Self-driven and willing to take ownership of specific tasks and analyses

  • 1-2 years' experience in a technical, analytical or data-focused role

Nice to Have

  • Exposure to credit risk or financial datasets

  • Interest in Data Engineering

  • Prior experience with financial or pricing modelling

The interview process

  • A phone call with one of the team

  • Video Call case study (Remote)

  • Onsite Interview

    • Culture Interview

    • Meet the team you'll work with daily

Life at Lendable

  • Winning team: the opportunity to scale up one of the world’s most successful fintech companies

  • Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites

  • Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls

  • Health coverage: support for your physical and mental wellbeing, including private health cover

  • Retirement & savings: long-term financial wellbeing through retirement savings plans

  • Employee referral programme: earn a competitive bonus when you refer successful new team members

  • Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations

  • Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations

Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.

Check out our blog!

How we rate this

Analyst at Lendable rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Credit RiskPricingMachine learningAnalyticsscikit-learnPythonSQL

Questions you could be asked

  1. Tell me about a project where credit risk was part of your work. What did you do?
  2. Tell me about a project where pricing was part of your work. What did you do?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where analytics was part of your work. What did you do?
  5. Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Credit Risk, Pricing, Machine learning, Analytics, and scikit-learn. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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