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Data Scientist (AI)

Reads like a ML Engineer role: putting models into production.

London · London, United Kingdom

Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Growth & Analytics › Credit & Data › UK Operations Analytics — team source
Department: Growth & Analytics › Credit & Data › UK Operations Analytics
From the employer’s posting
Apply at Lendable

What you’ll work on

Full posting
  • Improve the chatbot's quality and expand the account actions it can complete

  • Expand document extraction pipelines for faster, more accurate parsing

  • Design LLM-driven workflows that simplify case management

  • Find new manual work to replace with effective AI systems

  • Own solutions from prototyping through deployment, evaluation and monitoring

From the employer’s posting
Improve the chatbot's quality and expand the account actions it can complete autonomously.
Expand our in-house document extraction pipelines to make parsing faster and more accurate.
Design LLM-driven workflows that simplify case management.
Find new opportunities to replace manual work with effective AI systems.
Own solutions from discovery and prototyping through deployment, evaluation and monitoring.

What you’ll bring

All qualifications

Core experience

  • Strong engineering skills and experience building production systems
  • Hands-on experience using LLMs in real workflows
  • Experience designing and improving prompts, retrieval pipelines, agent workflows and evaluations
  • Understanding of business processes and where AI can simplify or automate them
  • Ability to structure ambiguous problems and make progress with partial information
Qualification wording
Strong engineering skills and experience building production systems.
Hands-on experience using LLMs in real workflows.
Experience designing and improving prompts, retrieval pipelines, agent workflows and evaluations.
An understanding of business processes and good judgement about where AI can simplify or automate them.
The ability to structure ambiguous problems, test hypotheses and make progress with partial information.

Tools in this posting

  • Python
Source — Tool mentions in context
- Build the best technology in-house: we use new data sources, machine learning and AI to make machines do the heavy lifting This role combines applied AI engineering, process design and hands-on Python development. You will work on loosely defined problems, test ideas quickly and turn the strongest ones into reliable services. In under a year, we built a chatbot across Loans, Credit Cards and Motor Finance that now handles more than 1 million customer chats a year at around a 70% resolution rate. It completes complex account actions autonomously, end to end, and we hold it to the same standard as our best operations agents.

About Lendable

Lendable is on a mission to build the world's best technology to help people get credit and save money.

In the employer’s words · Read in context · Company website ↗

Posting record

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Status in our records
Live
First seen by us
Oct 2, 2026 · 19 days ago
Recorded sightings
32
Last seen by us
Oct 21, 2026

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Job description

View original posting ↗

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

This role combines applied AI engineering, process design and hands-on Python development. You will work on loosely defined problems, test ideas quickly and turn the strongest ones into reliable services.

In under a year, we built a chatbot across Loans, Credit Cards and Motor Finance that now handles more than 1 million customer chats a year at around a 70% resolution rate. It completes complex account actions autonomously, end to end, and we hold it to the same standard as our best operations agents.

We have also built AI document parsers that process around 500,000 documents a year, and are trialling voice AI on our phone lines. You will help take these systems further and find the next high-impact processes to automate.

What you will do

  • Improve the chatbot's quality and expand the account actions it can complete autonomously.

  • Expand our in-house document extraction pipelines to make parsing faster and more accurate.

  • Design LLM-driven workflows that simplify case management.

  • Find new opportunities to replace manual work with effective AI systems.

  • Own solutions from discovery and prototyping through deployment, evaluation and monitoring.

What we are looking for

  • Strong engineering skills and experience building production systems.

  • Hands-on experience using LLMs in real workflows.

  • Experience designing and improving prompts, retrieval pipelines, agent workflows and evaluations.

  • An understanding of business processes and good judgement about where AI can simplify or automate them.

  • The ability to structure ambiguous problems, test hypotheses and make progress with partial information.

  • Clear communication and the ability to explain trade-offs and influence stakeholders.

Why join us

  • Work with LLMs, retrieval systems, agents and automation pipelines every day.

  • Join a small, autonomous team with meaningful ownership and decision-making power.

Interview process

  1. Introductory call

  2. Take-home exercise

  3. Take home debrief

  4. Case study

  5. Onsite final interview

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.

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Pay

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Location & working pattern

London, United Kingdom

- 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
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