Staff Machine Learning Scientist

🚀 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 ❤️

Hear from our UK team about what it's like working at Monzo ✨

📍Cardiff, London, or Remote UK | Salary £140-£175,000 + stocks + benefits | Hear from the team ✨

About our Machine Learning Team:

At Monzo, Machine Learning Scientists have ownership across the entire ML lifecycle, from from formulating ML problems to deploying models and monitoring their impact on key product and business metrics.

Our Machine Learning Scientists collaborate in cross-functional squads across Data, Engineering, Product, and Risk, tackling a broad range of issues including fraud detection and prevention, transaction monitoring for various suspicious activities, customer risk assessment, and operational tooling.

About our Machine Learning Team for Personalisation:

Personalisation is central to Monzo’s mission—to make money work for everyone. By delivering tailored recommendations, proactive insights, and intuitive experiences, we help customers make better financial decisions while strengthening their connection with the bank. Every model we build directly enhances the banking experience, making it more seamless, engaging, and rewarding.

Our Personalisation Data team brings together experts across four key disciplines: Analytics Engineers, Data Analysts, Machine Learning Scientists, and Data Scientists. As a Lead Machine Learning Scientist, you’ll develop models that make every customer interaction more relevant and timely, ensuring they receive products and services tailored to their needs.

From intelligent recommendations and predictive insights to seamless discovery and real-time personalisation, our Machine Learning Scientists tackle challenges that directly improve customer outcomes. Whether it’s surfacing the right savings product at the perfect moment, helping customers manage their spending, or simplifying financial planning, our work makes banking smarter, more intuitive, and truly customer-first.

What you’ll be working on:

As a Staff ML Scientist, you’ll be the one of the most senior Individual Contributor (IC) Machine Learning Scientist! This will give you a real opportunity to lead us into an exciting new phase of personalisation, utilising billions of rows of data and the learnings from your previous successes in designing and building advanced Machine Learning based systems for topics like personalisation, demand forecasting, workforce management, detection systems.

We’re talking about Deep Learning, Graph neural networks, transformers – you’ll have space to design the architecture that will help us take our real time systems to the next level.

Your day-to-day

As our most senior technical IC, you’ll be providing key technical leadership and shipping highly impactful ML-based solutions. You’ll be empowered to work across the collective identifying the most impactful areas and leading solution development.

You’ll work with our mission-oriented cross functional product squads, collaborating closely with product managers, data scientists, backend engineers and designers in an agile environment.

You’ll be expected to use your technical expertise to advise senior business stakeholders and help to set and advance our strategic direction across multiple squads.

You’ll also be a technical leader within the Machine Learning discipline, helping to steer technical work and drive up standards.

This will involve:

• Working with stakeholders across the organisation to identify and scope out the most impactful opportunities to tackle product challenges with Machine Learning.

• Bringing the learnings from your previous successes in designing and building advanced Machine Learning systems to lead advancements in our product development capabilities, for example utilising deep learning, graph-based, and sequence-based architectures.

• Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.

• Working closely with our MLOps team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.

You should apply if:

What we’re doing here at Monzo excites you!

• You have a multiple year track record of excellence leading the technical work of a team in the development and deployment of advanced Machine Learning models tackling real business problems, 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 experience in, and a passion for, mentoring other ML practitioners, 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 tackle them without being told to do so

• Using advanced machine learning techniques to minimise financial crime and protect customers from fraud 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’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity

• you want to be involved in building a product that you (and the people you know) use every day

• you have a product mindset: you care about customer outcomes and you want to make data-informed decisions

• You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain

• You’re adaptable, curious and enjoy learning new technologies and ideas

The interview process:

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

• 4 x 1-hour video calls with various team members

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

What’s in it for you:

✈️ We can help you relocate to the UK

✅ We can sponsor visas

📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).

⏰ 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

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.

#LI-REMOTE #LI-NJ1

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, 2024 Diversity and Inclusion Report and 2024 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 😊