Lead Machine Learning Scientist, Customer Operations

🚀 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 ❤️

📍London/Cardiff/UK Remote | 💰 £115,000 - £150,000 + Incentive Awards tied to your performance + Benefits ✨

About our Machine Learning Operations team:

The challenges are significant: we aim to transform customer service by reducing the time and effort required to resolve issues, enhancing customer confidence and satisfaction. As part of Operations, you’ll be at the forefront of our mission to provide unparalleled customer support experiences.

Your role will be pivotal in leveraging state-of-the-art machine learning techniques (including LLMs and autonomous agents) to understand customer problems. You will lead the development of an effective human-in-the-loop system that augments automation with the efforts of our support workforce (who we call COps). This allows us to more expediently and efficiently predict, identify, disambiguate, and route customer problems at scale to support a rapidly expanding company with global ambitions across multiple geographies.

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

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 wider 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 transform Customer Operations with Machine Learning.

Leading the design and development of advanced Machine Learning models, exploring how LLMs, RAG, and sequence-based architectures can drive improvements in query resolution and routing.

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

Steering ongoing technical strategy, working closely with our MLOps team and backend engineers 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 deep learning, graph-based, and/or sequence-based 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