Monzo

LeadMachineLearningScientist

£105–140k Cardiff, United Kingdom; London, United Kingdom; United Kingdom Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Machine Learning Scientist at Monzo. Skills: Machine Learning models, Python, SQL, technical leadership. develop models that make every customer interaction more relevant and timely. making sure the approach meets our business and customer needs”

What You'll Achieve.

making every customer interaction more relevant and timely; ensuring they receive products and services tailored to their needs; improve customer outcomes; making banking smarter, more intuitive, and truly customer-first; deliver personalised user experiences; measurable impact in production

Industry & Context.

Problems you'll solve

tackle business problems; resolve that ambiguity

What They're Looking For.

Must Have

extensive experience writing production Python code, command of SQL

Nice to Have

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

What You'll Do.

develop models that make every customer interaction more relevant and timely

making sure the approach meets our business and customer needs

shipping highly impactful ML-based solutions

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

steering the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle

How You'll Work.

Team & Collaboration

embedded in a cross functional product squad; working closely with product managers, data scientists, backend engineers and designers in an agile environment; technical leader within the Machine Learning discipline; Working with stakeholders across the organization

Communication Scope

communicate those ideas to colleagues who are not familiar with the domain

Full Job Description

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 exp

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