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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Remote Senior Machine Learning Scientist, Borrowing - **Company:** Monzo - **Location:** Manchester, UK (Remote available) - **Experience:** Expert - **Salary:** £86,000.0 - £105,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, BigQuery, Bootstrap (Software), Cloud Computing, Information Engineering, Statistical Hypothesis Testing, Python (Programming Language), Logistic Regression, Machine Learning, Software Engineering, SQL Databases, Google Cloud, Model Validation, Backend, GPT, Microservices - **Published:** June 25, 2026 - **Apply:** https://find.jobs/jobs-near-me/remote-senior-machine-learning-scientist-borrowing-manchester/2840388705-2/ ## About the Role * You are result oriented and motivated by the impact on our customers and business * You enjoy a high degree of autonomy and thrive in a fast-paced environment * You are keen to grow your knowledge in both business and technology You must have: * Excellent SQL and Python skills with good understanding of best practices in software engineering and data engineering * In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc * Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap * Experience of end-to-end model development and maintenance of ML models used for business critical automated decisioning, in a consumer facing industry * Great attention to details while keeping an eye on the big picture * Excellent communication skills to articulate complex problems * Capability to build mutual respect and trust with people of different background Nice to have: * Experience in UK/EU retail lending businesses for personal/business customers * Experience of ML model governance in a regulated industry * Experience in leverage modern day AI tools for productivity ## Description The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing. You will be working alongside a team of very experienced and highly efficient ML Scientists, with well established toolings for the fully lifecycle of ML models. Each of you owns multiple ML applications end-to-end, from experiment design and data curation, to deployment and monitoring. You will be empowered to innovate in the data, methodologies and toolings, so we can build better models easier and faster. You will have exposure to all Borrowing products and applications, with autonomy to decide what are the most impactful topics to work on, and how to deliver them. You will work closely with our Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers, to fit your model development into the product roadmap. You are also empowered to think big about the business, market and customers, to influence our product and credit strategy beyond just the world of models. Our technology stack We rely heavily on the following tools and technologies (although we do not expect applicants to have prior experience of all them): * Google Cloud Platform for all of our analytics usages + BigQuery SQL and dbt for our data modelling and warehousing + PyData stack for model development and offline deployment + Google Vertex AI platform for cloud computing * AWS for backend infrastructure + Python for ML model microservices + Go lang for most other microservices * AI toolings for productivity (an evolving list) + Google suites including access to Gemini + ChatGPT enterprise + Claude code ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [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) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [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) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [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) - [Best Companies to work for in London: Top 25 Companies in 2023](https://www.wearedevelopers.com/magazine/187-best-companies-to-work-for-in-london-top-25-companies-in-2023) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)