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Home›Jobs›Lendable›Junior Data Scientist
Lendable

About Lendable

Profitable Fintech Unicorn - Lending Made Easy

🏢 Tech, Finance, Financial Services👥 201-500 employees📅 Founded 2014📍 London, UK💰 $290.4m⭐ 4.4
FintechB2CMarketplacePersonal financeLendingCustomer service

Key Highlights

  • Headquartered in London, UK with 201-500 employees
  • $290.4 million raised from institutional investors
  • Streamlines loan applications, reducing fund transfers to minutes
  • Launched two new products in the US market

Lendable is a profitable fintech unicorn headquartered in London, UK, specializing in consumer lending. With $290.4 million raised from institutional investors, Lendable streamlines the loan application process, reducing fund transfers from days to minutes. The company has launched two new products ...

🎁 Benefits

Lendable offers comprehensive private health insurance, including dental and optometry, along with best-in-class compensation packages that include eq...

🌟 Culture

Lendable's culture is centered around customer service excellence and financial strength, allowing it to compete effectively against banks and other l...

🌐 Website💼 LinkedIn𝕏 TwitterAll 55 jobs →
Lendable

Junior Data Scientist

Lendable • London

Posted 1 month agoJuniorData scientist📍 London
Apply Now →

Job Description

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 newest unicorns with a team of just over 600 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 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 in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo

  3. Build the best technology in-house, using 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 USP, 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 strategies and modelling methodology

  • 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

  • Confident communicator and contributes effectively within a team environment

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

Nice to Have

  • Interest in Data Engineering

  • Exposure to credit risk or financial datasets

  • Prior experience with financial modelling

The interview process

  • A phone call with one of the team

  • A take home task to complete in your own time

  • Task Debrief

  • Video Call case study (Remote)

  • Onsite Interview

    • Culture Interview

    • Meet the team you’ll work with daily

Life at Lendable

  • The opportunity to scale up one of the world’s most successful fintech companies.

  • Best-in-class compensation, including equity.

  • You can work from home every Monday and Friday if you wish - on the other days, those based in the UK come together IRL at our Shoreditch office in London to be together, build and exchange ideas.

  • Enjoy a fully stocked kitchen with everything you need to whip up breakfast, lunch, snacks, and drinks in the office every Tuesday-Thursday.

  • We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance

  • We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London

Check out our blog!

Interested in this role?

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