Senior Machine Learning Scientist, Borrowing

Monzo; Cardiff; Hybrid; GBP 93,000 - 120,000; Full time

Benefits offered by this job

Stock options

Relocation assistance

Visa sponsorship

Hybrid/remote UK

MacBooks provided

Learning budget

Job summary

Monzo is hiring a Borrowing ML Scientist to improve customer outcomes through automated decisioning in credit risk. You will join a team of experienced ML Scientists and own multiple models end-to-end, from data curation to deployment.

The role offers hybrid or remote work within the UK, relocation and visa sponsorship, a learning budget, and stock options. You will work with Credit Strategy, Validation, and Product teams to influence product decisions.

Qualifications

• Excellent SQL and Python skills with best practices in software engineering and data engineering.
• In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis.
• Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap.
• Experience of end-to-end model development and maintenance of ML models used for business critical automated decisioning.

Responsibilities

• Own multiple ML applications end-to-end from experiment design and data curation, to deployment and monitoring.
• Collaborate with Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers to fit your model development into the product roadmap.
• Empower to think big about the business, market and customers to influence our product and credit strategy beyond just the models.

Skills

SQL

Python

Statistical ML models

End-to-end ML development

Model deployment

Experiment design

Communication

Team collaboration

Tools

Google Cloud Platform

BigQuery

dbt

Vertex AI

AWS

Python

Go

Job description

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 | £93,000-120,000 + Incentive Awards tied to your performance + benefits | Hear from the team

About us:

At Monzo we want to make money work for everyone. We care deeply about our 15+ million customers. Through magically simple products and actionable insights, we put our customers in control of their finance. Our products are different by design, and reliable at our core.

Our range of borrowing products are critical to Monzo’s mission. Not only do they serve important needs of our customers, they are also a key revenue driver to support Monzo keep delivering great products and experience. We have seen stellar growth and deep engagement with millions of borrowers, supported by effective and efficient credit risk management. Our product portfolios are still expanding fast, from personal to business credit, and markets beyond UK. We are looking for bright, passionate and creative individuals to further accelerate our growth.

About the role

The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing.

You will be working alongside a team of very experienced and highly efficient ML Scientists, with well established toolings for the fully lifecycle of ML models. Each of you owns multiple ML applications end-to-end, from experiment design and data curation, to deployment and monitoring. You will be empowered to innovate in the data, methodologies and toolings, so we can build better models easier and faster.

You will have exposure to all Borrowing products and applications, with autonomy to decide what are the most impactful topics to work on, and how to deliver them. You will work closely with our Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers, to fit your model development into the product roadmap. You are also empowered to think big about the business, market and customers, to influence our product and credit strategy beyond just the world of models.

Our technology stack

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

• Google Cloud Platform for all of our analytics usages
  • BigQuery SQL and dbt for our data modelling and warehousing
  • PyData stack for model development and offline deployment
  • Google Vertex AI platform for cloud computing
• AWS for backend infrastructure
  • Python for ML model microservices
  • Go lang for most other microservices
• AI toolings for productivity (an evolving list)
  • Google suites including access to Gemini
  • ChatGPT enterprise
  • Claude code

You should apply if:

• You are result oriented and motivated by the impact on our customers and business
• You enjoy a high degree of autonomy and thrive in a fast-paced environment
• You are keen to grow your knowledge in both business and technology

You must have:

• Excellent SQL and Python skills with good understanding of best practices in software engineering and data engineering
• In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc
• Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap
• Experience of end-to-end model development and maintenance of ML models used for business critical automated decisioning, in a consumer facing industry
• Great attention to details while keeping an eye on the big picture
• Excellent communication skills to articulate complex problems
• Capability to build mutual respect and trust with people of different background

Nice to have:

• Experience in UK/EU retail lending businesses for personal/business customers
• Experience of ML model governance in a regulated industry
• Experience in leverage modern day AI tools for productivity

The Interview Process:

Our interview process involves:

• 30’ Recruiter Call
• 45’ Initial Call
• 60’ ML technical skill interview
• 60’ Behavioural interview

All interviews will be conducted through Google Meet.

What’s in it for you:

£93,000 to £120,000 plus stock options & benefits

We can help you relocate to the UK

We can sponsor visas

This role can be either based in our London office with hybrid working pattern, or fully remote within UK with occasional travels to London.

We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.

We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.

Learning budget of £1,000 a year for books, training courses and conferences

And much more, see our full list of benefits here

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.