Machine Learning Manager, Operations

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 | 💰£113,200 - £153,200 + equity + Incentive Awards tied to your performance + Benefits  ✨

We’re building the machine learning and optimisation systems that help Monzo provide fast, efficient and resilient customer support at scale.

You’ll lead Machine Learning for our Workforce Management vertical: the organisation that makes sure Monzo has the right human support supply to meet customer demand. The team works on demand forecasting, real-time supply <> demand matching, problem routing and escalation, and predictive models that help us understand how long work will take, what might become late, and where the next best human support should be assigned.

This is a great role for someone who is still close to technical work. You might be a Tech Lead, Team Lead, Senior Machine Learning Scientist or Senior Machine Learning Engineer who has recently been building models and systems yourself, and is excited to grow into a broader leadership role.

Not everything here is about LLMs. You’ll work on rigorous ML, forecasting, optimisation and operations research problems where quantitative thinking, pragmatic delivery and strong product judgement really matter.

You’ll lead a growing team of Machine Learning Scientists, embedded in product squads working alongside data scientists, backend, mobile and web engineers, product managers, user researchers, designers and operations specialists.

• Shaping the ML strategy for Workforce Management, helping us decide where ML, forecasting and optimisation can have the biggest impact for customers and human agents.
• Leading the design, build and delivery of production ML systems across forecasting, routing, assignment, escalation and time-to-completion prediction.
• Staying close to the technical details: helping the team frame problems well, choose the right modelling approach, define robust validation, review trade-offs and ship safely.
• Working with Product, Engineering, Data and Operations leaders to turn ambiguous operational problems into pragmatic, iterative ML systems that improve real customer outcomes.
• Coaching and developing Machine Learning Scientists through regular 1:1s, feedback and technical guidance.
• Creating healthy ways of working for the team: clear priorities, strong technical standards, good documentation, sensible monitoring, and space for people to do their best work.
• Contributing to the wider Machine Learning discipline at Monzo, helping us scale how we build, ship and operate ML systems in production.

• You’ve recently worked as a hands-on Machine Learning practitioner, for example as a Senior IC, Tech Lead, Team Lead or ML manager.
• You have strong foundations in ML, statistics, forecasting, optimisation or operations research, and enjoy applying them to messy real-world problems.
• You’ve built, shipped or owned ML systems in production, and understand what it takes to make models useful, reliable, monitored and safe.
• You can move between technical detail and business context, explaining complex ML ideas clearly to technical and non-technical people.
• Coaching others is something you enjoy and take seriously. You may already have people management experience, but we’re also open to people taking their first formal step into management.
• Ambiguous problem spaces energise you. The right answer might involve a model, an algorithm, a product change, an operational process, or a combination of all four.
• Customer outcomes matter to you, and you want to build systems that help people get answers to their problems quickly and efficiently.
• You’re adaptable, curious and excited by quantitative problems.

Not ticking every box? That’s totally okay! Studies show that women and people of colour might hesitate to apply unless they meet every single requirement. At Monzo, we’re dedicated to creating a diverse and welcoming team. If you’re passionate about this role and keen to learn and grow with us, we encourage you to apply— even if you don’t have everything that's listed just yet. Drop us your application, we’d love to hear from you!

💰 £113,200 - £153,200 ➕Incentive Awards tied to your performance.

✈️ We’ll help you relocate to the UK.

✅ We can sponsor your visa. 

📍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, and at times that suit you and your team. 

📚 £1,000 learning budget each year to use on books, training courses and conferences.

🏡 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. 

➕ Plus lots more! Read our full list of benefits.

• Recruiter Call
• Initial Call
• Full Loop

This process should take around 3-4 weeks - your schedule is really important to us, so we promise to be as flexible as possible! 

We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo. You can read them here.

#LI-REMOTE

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.

If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊