Lead Machine Learning Scientist, Business Banking

ProfilHQ; Greater London; Hybrid; GBP 115,000 - 150,000; Full time

Benefits offered by this job

Relocation assistance

Visa sponsorship

Flexible working hours

Learning budget

Job summary

Monzo is seeking a Lead Machine Learning Scientist for Business Banking to drive ML and GenAI capabilities for small businesses. You will lead and ship models that power customer experiences, collaborating with product, data science and engineering teams across the UK.

You will design end-to-end ML solutions, from problem framing to production deployment, ensuring measurable business impact while maintaining responsible AI practices. Remote-friendly with relocation and visa support.

Qualifications

• Proven track record leading the development and deployment of advanced ML models.
• Experience shipping ML models to production with measurable business impact.
• Own end-to-end ML lifecycle from problem framing to monitoring.

Responsibilities

• Lead ML Scientist in Business Banking, shipping ML/GenAI capabilities.
• Develop and deploy advanced ML models on cloud-native data platform.
• Partner with Product, data science and other stakeholders to identify high-impact opportunities.
• Design robust evaluation and monitoring for responsible ML and AI.
• Collaborate with MLOps and Backend Engineering to operationalise models end-to-end.
• Set technical standards, mentor others, and support experimentation and iteration.
• Shape product strategy with stakeholders and ensure customer value.

Skills

Python

SQL

Go

GenAI

Leadership

Product mindset

Communication

ML deployment

Tools

scikit-learn

Job description

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 Business Banking team

Our mission in Business Banking is to simplify banking for small businesses; making business banking fairer, simpler and more transparent. Monzo Business Banking is fast-growing, is the UK’s most recommended business account for overall service quality. We recently hit 1 million customers and are used by 1 in 6 UK SMEs.

We want to help businesses spend less time on financial admin and more time focused on running and growing their business. We’re building intelligent, data-driven and AI/ML-enabled product experiences that help small businesses feel more in control, make better decisions, and get more value from Monzo.

ML is at the core of how we build and scale our products, enabling Monzo to make better decisions, faster, and helping us serve businesses more effectively.

As a Lead Machine Learning Scientist in Business Banking, you’ll help build and ship models that power the next generation of Business Banking experiences. You’ll work closely with Product, Engineering, Design, Research, Data Science and Analytics Engineering to bring ML-enabled product capability into the heart of how we build for businesses.

Whether it’s helping businesses understand their cash flow, reducing manual admin, surfacing the right insight at the right moment, or helping teams build intelligent product experiences responsibly, our work makes business banking smarter, simpler and more useful for SMEs.

What you'll be working on

As a Lead Machine Learning Scientist, you’ll be a technical leader and hands-on individual contributor, spearheading our ML and GenAI capabilities and shipping key models that powers magical Business Banking experiences.

You’ll:

• Be one of the first ML Scientists in Business Banking, bringing leadership through ambiguity by adding structure and direction to our ML capabilities while staying agile and building momentum.
• Develop and deploy advanced ML models on our cloud-native data platform to serve hundreds of thousands of business customers.
• Partner with Product, data science and other stakeholders to identify the highest-impact opportunities, size impact, and define success metrics.
• Decide when to use ML, GenAI, or simpler approaches and be clear on trade-offs.
• Design robust evaluation and monitoring so we can ship responsibly and measure impact in production.
• Lead the design and implementation of batch and near-real-time models (e.g. LLM-powered experiences, predictive models, time-series forecasting).
• Collaborate closely with MLOps and Backend Engineering to operationalise models end-to-end and raise the bar on ML lifecycle rigor.
• Set technical standards, mentor others, and support experimentation and iteration.

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 models 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 speak Python fluently and have extensive, hands-on experience with scikit-learn . You are comfortable using SQL, and keen to learn Go, 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 small businesses use to run and manage their financial lives 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 AI 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.
• You’re excited by the opportunity to help Business Banking evolve into AI and ML-enabled product capability.
• You can work closely with Product, Engineering, Design, Research and Data colleagues to shape product strategy, clarify trade-offs and build things that customers actually use.
• You’re thoughtful about responsible ML/AI; especially in financial products where trust, transparency and customer control matter.

Nice to haves

• Experience working on personalisation, ranking, recommendation, forecasting, classification or decisioning problems for customer-facing applications.
• Experience working on ML systems for fintech, banking, accounting, payments, lending, invoicing, cash flow, tax, risk or business software.
• Experience with GenAI, LLMs, agentic workflows, retrieval, evaluation frameworks, or human-in-the-loop product experiences.
• Commercial experience writing critical production code and working with microservices.
• Experience designing experiments, A/B tests or other approaches to measure product and customer impact.
• Experience working in regulated environments or with products where explainability, auditability and customer trust are especially important.

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

Full Loop: ML Modelling Interview, Product & ML interview, Behavioural Interview, Leadership interview

Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on [e-mail] . Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason.

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 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 happening whenever we can - whether this is to help you meet other commitments or strike a great work-life balance

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 , 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