Lead Machine Learning Scientist

London/Cardiff/UK Remote | 💰 £105,000 - £140,000 + Benefits | ✨

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:

A Lead Machine Learning Scientist at Monzo is a technical Individual Contributor (IC) leadership position. As a technical Machine Learning expert, working with billions of rows of data stored on a modern cloud native data platform, we’ll be expecting you to leverage your deep experience of developing and deploying advanced Machine Learning models.

Your work may involve segmentation models to better understand customer behaviors, contextual bandits for optimising real-time decisions, or personalised ranking algorithms that improve search and discovery. You'll also build scalable, explainable, and responsible AI solutions that enhance trust, transparency, and the overall customer experience.

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

Your day-to-day:

As a technical individual contributor, you’ll be providing technical leadership and shipping highly impactful ML-based solutions. You’ll be embedded in a cross functional product squad, working closely with product managers, data scientists, backend engineers and designers in an agile environment. 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 organization to identify and scope out the most impactful opportunities to tackle business problems in personalisation.
• Leading the design and development of advanced real time Machine Learning models, for example exploring how recent advances in machine learning (neural network, graph-based, and sequence-based architectures, LLMs) can drive improvements in our ability to deliver personalised user experiences.
• 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 ML platform 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 development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
• You have experience developing and shipping state of the art ML architectures to production and delivering business impact
• 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 self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• 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

Nice to haves:

• Experience working on personalisation problems for consumer applications
• Commercial experience writing critical production code and working with microservices

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
• 1 take home task
• 3 x 1-hour video calls with various team members

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.