Overview

We’re on a mission to make money work for everyone. Monzo aims to simplify banking and deliver value through innovative products and services. Our Machine Learning Scientists own the full ML lifecycle, from formulating problems to deploying models and monitoring impact on product and business metrics.

In the Personalisation team, we build models that deliver tailored recommendations and proactive insights to enhance the customer experience and decision making. Our cross-functional squads include Data, Engineering, Product, and Risk, tackling fraud detection, transaction monitoring, customer risk, and operational tooling.

What you’ll be working on

As a Senior Lead ML Scientist, you’ll be one of the most senior individual contributors in the ML discipline. You will lead advancements in fraud and financial crime prevention using billions of rows of data and past learnings from designing and building advanced ML systems for personalisation, demand forecasting, workforce management, and detection systems. You’ll work with architectures such as deep learning, graph neural networks, and transformers to elevate our real-time systems. You’ll provide technical leadership and ship highly impactful ML-based solutions, identifying the most impactful areas and leading solution development.

You’ll collaborate with mission-oriented cross-functional product squads—product managers, data scientists, backend engineers, and designers—in an agile environment. You’ll advise senior business stakeholders and help set strategic direction across multiple squads. You’ll also act as a technical leader within the ML discipline, driving standards and mentoring others.

This will involve:

• Engaging stakeholders to identify and scope high-impact opportunities where ML can solve product challenges.
• Bringing learnings from previous successes to lead advancements in product development using deep learning, graph-based, and sequence-based architectures.
• Providing technical leadership to raise technical capability and best practices across the ML discipline.
• Working with the MLOps team to steer tool development enabling rapid iteration and lifecycle optimization of models.

You should apply if

What we’re doing at Monzo excites you!

• You have a multi-year track record of leading technical work in developing and deploying advanced ML models that solve real business problems, preferably in a fast-moving tech company.
• You are impact-driven and own end-to-end outcomes from problem to measurable production impact.
• You have experience mentoring ML practitioners and raising the technical bar across teams.
• You are a self-starter who proactively identifies and tackles high-impact issues.
• You are excited by using ML to minimise financial crime and protect customers from fraud.
• You have extensive experience writing production Python code and strong SQL skills; comfortable with them daily and keen to learn Go for backend services.
• You are comfortable navigating ambiguity and helping teams and stakeholders resolve it.
• You want to build a product you and others use every day with a customer-focused mindset.
• You are enthusiastic about fast-moving ML developments and can communicate those ideas to non-experts.
• You are adaptable, curious, and enjoy learning new technologies.

The interview process

Our interview process involves three main stages with a commitment not to ask brain teasers or trick questions:

• 30-minute recruiter call
• 45-minute interview with the hiring manager
• Four 1-hour video calls with various team members

Average process duration is 3–4 weeks. You can speak with our recruitment team at various points. For questions, contact tech-hiring@monzo.com. We can accommodate adjustments for disability, neurodiversity, or other personal reasons.

What’s in it for you

Relocation assistance to the UK may be available, and visa sponsorship is possible. The role can be based in London or work distributed within the UK with occasional London visits. Flexible hours and a learning budget of £1,000 per year for books, training, and conferences. See the full benefits list for more details. Part-time arrangements may be possible where feasible.

#LI-REMOTE #LI-NJ1

Equal opportunities

Diversity and inclusion are priorities at Monzo. We are an equal opportunity employer and encourage applications from people of all backgrounds. We support an inclusive environment to help everyone thrive. You can read more in our Diversity and Inclusion Report and Gender Pay Gap Report.

If you have a preferred name, please use it when applying. We do not require full or birth names at the application stage.