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Senior Machine Learning Manager, Borrowing

Monzo

Remote · Cardiff, London or, United KingdomFull Time

Senior Machine Learning Manager, Borrowing at Monzo is a full time role based in Remote · Cardiff, London or, United Kingdom (remote). It was published on 24 June 2026 and was open at last check.

Senior Machine Learning Manager, Borrowing at Monzo — key details
RoleSenior Machine Learning Manager, Borrowing
CompanyMonzo
LocationRemote · Cardiff, London or, United Kingdom (remote)
Employment typeFull Time
Published24 June 2026
StatusOpen at last check

🚀 We’re on a mission to make money work for everyone.

We’re waving goodbye to the complicated and confusing ways of traditional banking.

After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us.

With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers!

We’re not about selling products - we want to solve problems and change lives through Monzo ❤️

📍London/Cardiff/UK Remote | 💰 £138,000 to £176,000 + Incentive Awards tied to your performance + benefits | Hear from the team

About the role

Borrowing is one of Monzo’s most important growth engines. We’ve built strong scale in the UK, and the next phase is even more ambitious: grow in the UK, expand into new customer segments, and build the underwriting capability needed to scale into Europe.

We’re looking for a senior ML leader to help shape that next phase.

You’ll lead a high-calibre team of ML scientists and help define Borrowing’s ML roadmap across UK growth, new customer segments, and EU expansion. You’ll work across underwriting, pricing, limits, and lifecycle decisioning — improving today’s models while helping build the next generation of capability for Monzo.

This role combines near-term commercial impact with long-term strategic advantage:

  • improving performance across our range of products
  • unlocking new data and faster model development
  • helping Monzo build underwriting that scales into new markets
  • shaping how advanced ML and AI can create real value in Borrowing

You’ll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo.

What you’ll own

  • Borrowing ML roadmaps across UK optimisation, new customer segments, and EU expansion
  • Faster model improvement through new data and feature engineering
  • How Monzo uses Open Banking, transaction intelligence, and external data in credit decisioning
  • More portable underwriting capabilities across products, customer segments, and markets
  • Hiring, leading, and developing a high-performing ML team
  • Raising the bar on model quality, governance, tooling, and speed of iteration

What you’ll be working on

Examples of the challenges you could help lead:

  • Improving underwriting models across Loans, Flex, and Overdrafts
  • Expand the data we use in our models
  • Building better feature engineering and model shipping capability
  • Improving transaction intelligence for credit use cases
  • Developing underwriting capabilities for new customer segments and EU markets
  • Shaping Monzo’s approach to advanced ML and AI

Our technology stack

We rely heavily on the following tools and technologies, although we do not expect applicants to have prior experience of all of them:

  • Google Cloud Platform
  • BigQuery SQL and dbt
  • Python and the PyData stack
  • Google AI Platform
  • AWS
  • Python for ML services
  • Go for backend services
  • AI tooling for productivity
  • Google Workspace including Gemini
  • ChatGPT Enterprise
  • Claude Code

You should apply if

  • You want to shape the next phase of credit decisioning at one of Europe’s most ambitious fintechs
  • You enjoy combining strategic leadership with strong technical judgment
  • You’re excited by the intersection of underwriting, data, product, and platform capability
  • You like building teams as much as building models
  • You care about real customer and business impact

You must have

Credit and machine learning

  • Strong knowledge of machine learning, statistics, and decisioning systems
  • Deep experience in credit risk and lending
  • Experience building, deploying, and iterating credit models in production
  • Experience pushing the innovation frontiers of the credit industry

Leadership and delivery

  • Experience leading and developing senior ML scientists
  • Strong cross-functional leadership with Product, Credit Strategy, Engineering, and Validation
  • Track record of turning strategy into practical delivery in a regulated environment

It would be great if you also have

  • Experience across more than one market
  • Experience with advanced ML methods and AI on structured financial data

The interview process

  • 30 min Recruiter Call
  • 45 min Initial Call
  • 60 min ML technical interview
  • 60 min People Leadership interview
  • 60 min Product / Credit ML interview

All interviews will be conducted through Google Meet.

What’s in it for you

💰 £138,000 to £176,000 ➕ plus stock options & benefits

✈️ We can help you relocate to the UK

✅ We can sponsor visas

📍This role can be based in our London office with a hybrid working pattern, or fully remote within the UK with occasional travel to London.

🏡 We’ll set you up to work from home, including support for remote setups.

⏰ We offer flexible working hours and trust you to work in a way that lets you do your best work.

📚 Learning budget for books, training courses and conferences

➕ And much more — see our full list of benefits here

#LI-DC2 #LI-Remote


Equal opportunities for everyone

Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report.

We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊

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Create your free OnJob profile to apply — we'll take you to Monzo's application after sign-up. · Posted 24 Jun 2026.

Senior Machine Learning Manager, Borrowing at Monzo — questions answered

What does the Senior Machine Learning Manager, Borrowing role at Monzo pay?

Monzo does not publish a salary on this Senior Machine Learning Manager, Borrowing listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.

Is the Senior Machine Learning Manager, Borrowing role at Monzo remote?

Yes — Monzo advertises this Senior Machine Learning Manager, Borrowing role as remote, tied to Remote · Cardiff, London or, United Kingdom, and it is listed as full time work. Remote terms come from the employer's own posting, so confirm the expected working hours, timezone and any on-site days with Monzo before you apply.

Is the Senior Machine Learning Manager, Borrowing role at Monzo still open?

The Senior Machine Learning Manager, Borrowing posting at Monzo was open at OnJob's last check of the employer's careers page, having been published on 24 June 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.

How do you apply for the Senior Machine Learning Manager, Borrowing role at Monzo?

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