> Markdown version of [/jobs/ext/2063249-lead-machine-learning-scientist-business-banking](https://www.wearedevelopers.com/jobs/ext/2063249-lead-machine-learning-scientist-business-banking). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Machine Learning Scientist, Business Banking - **Company:** Monzo - **Location:** London, UK (Remote available) - **Experience:** Expert - **Salary:** £56,481.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Business Software, Python (Programming Language), Machine Learning, SQL Databases, Large Language Models, Generative AI, Backend, Scikit Learn, Production Code, Machine Learning Operations, Microservices - **Published:** August 15, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5840392097 ## About the Role * 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., * 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. ## Description 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., 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). ## Related Videos - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Is my AI alive but brain-dead? How monitoring can tell you if your machine learning stack is still performing](https://www.wearedevelopers.com/videos/262-is-my-ai-alive-but-brain-dead-how-monitoring-can-tell-you-if-your-machine-learning-stack-is-still-performing) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)