Quick Summary
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 700 people Among the…
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 700 people
Among the fastest-growing tech companies in the UK
Profitable since 2017
Backed by top investors including Balderton Capital and Goldman Sachs
About the Role
~1 min readThe data science team develops proprietary machine learning models combining state-of-the-art techniques with a variety of data sources that inform scorecard development and risk management, optimise marketing and pricing, and improve operations efficiency.
Research new data sources and unstructured data representation.
Data scientists work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.
Deliver data services to a wide variety of stakeholders by engineering CLI programs / APIs.
Design, implement, manage and evaluate experiments of products and services leading to constant innovation and improvement.
Use your expertise to build and deploy models that contribute to the success of the business.
Stay up to date with the latest advancements in machine learning and credit risk modelling proactively proposing new approaches and projects that drive innovation.
Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling.
Extract, parse, clean and transform data for use in machine learning.
Clearly communicate results to stakeholders through verbal and written communication.
Mentor other data scientists and promote best practices throughout the team and business.
Knowledge of machine learning techniques and their respective pros and cons.
Ability to communicate sophisticated topics clearly and concisely.
Proficiency with creating ML models in Python with experiment tracking tools, such as MLFlow.
Curiosity, creativity, resourcefulness and a collaborative spirit.
Interest in problems related to the financial services domain - a knowledge of loan or credit card underwriting is advantageous.
Confident communicator and contributes effectively within a team environment.
Experience mentoring or leading others.
Self-driven and willing to lead on projects / new initiatives.
Familiarity with data used within credit risk decisioning such as Credit Bureau data, especially across multiple geographies is an advantage.
We’re not corporate, so we try our best to get things moving as quickly as possible. For this role, we’d expect:
A quick phone call with the people team
Interview with hiring manager
Take home task
Task debrief
Case study interview
In person interview where you'll do your final round and have some lunch with the team
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!
Location & Eligibility
Listing Details
- Posted
- October 16, 2025
- First seen
- May 7, 2026
- Last seen
- May 7, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 16%
- Scored at
- May 7, 2026
Signal breakdown
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