Senior Machine Learning Scientist, FinCrime

Cardiff, London or Remote UK | Salary 93,000 - 120,000 + Incentive Awards tied to your performance+ benefits | Hear from the team

You'll play a key role by:

This role sits as part of a multidisciplinary squad, collaborating with other Machine Learning Scientists, Data Scientists, Backend Engineers, Operations specialists, Product managers, and Risk managers. You'll play a key role by leveraging your deep experience of developing and deploying advanced Machine Learning models as to:

• Automatically and accurately detect suspicious user behaviours while minimising impact to genuine customers and operational costs.
• Adapt quickly and appropriately to changing fraud and financial crime trends, ensuring our detection systems remain performant through time.
• Design machine learning solutions that scale globally.

The technical approaches you take to solve these problems will be very much in your hands and well strongly encourage and support experimentation and innovation. Well be expecting you to justify and demonstrate effectiveness along the way, making sure the approach meets our business and customer needs.

You should apply if:

What were doing here at Monzo excites you!

• You have a track record of deploying advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company.
• You're impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production.
• You have a passion for sharing knowledge and raising the technical bar across the team.
• You have a self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so.
• Using advanced ML techniques to ensure Monzos customers money stays safe, even if their card, phone or account is compromised, sounds exciting to you.
• You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices.
• You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact.
• You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ambiguity.
• You have strong communication skills and are able to explain complex technical concepts to non-technical stakeholders
• You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and >Read our full list of benefits.

  Our interview process involves 3 main stages.

  We promise not to ask you any brain teasers or trick questions!

  • 30 minute recruiter call
  • 45 minute call with hiring manager
  • 60 minute ML Modelling interview
  • 60 minute Product & ML interview
  • 60 minute behavioural interview

  Our average process takes around 3-4 weeks but we will always work around your availability.

  You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on tech-hiring@monzo.co

  #LI-REMOTE #LI-SR1

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  Equal opportunities for everyone

  Diversity and inclusion are a priority for us and were making sure we have lots of support for all of our people to grow at Monzo. At Monzo, were 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.

  Were 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