Senior Machine Learning Manager, Borrowing

About the role

You define the machine learning strategy for Borrowing, directly influencing UK growth and European entry. Your responsibilities will shape how credit products perform and ensure models serve customers responsibly. This position requires you to own the end-to-end ML lifecycle for borrowing, from strategic planning to production deployment. You will translate business objectives into technical roadmaps and lead their execution. The role demands a balance between immediate impact and long-term strategic vision. You will act as a technical leader guiding complex initiatives through ambiguity to successful completion. Collaboration across disciplines will be central to your daily work as you synthesize input from product, risk, and engineering. Your decisions will have a direct impact on the financial health and customer experience of the borrowing business.

Key facts

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Location: Cardiff

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Engagement: Full-time

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Compensation: £138,000 to £176,000 plus performance-based awards

What you'll do

You will set the machine learning roadmap to optimize UK performance and enable expansion into new customer segments. This involves designing and running experiments to validate new data sources and advanced feature engineering techniques. You will guide the integration of Open Banking and transaction intelligence into credit decisioning frameworks. A core part of your role is shipping models by collaborating closely with engineering teams and rigorously validating model behavior prior to release. You will partner with Credit Strategy and Product to define and enhance underwriting capabilities. This includes elevating model quality standards and accelerating the iteration pace across the team. Another key responsibility is building hiring plans that attract top-tier ML scientists to the Borrowing organization. You will also champion robust governance frameworks to ensure ML workflows remain reliable, transparent, and auditable.

Specific responsibilities include leading the development of underwriting models for loans, Flex, and overdraft products. You will be responsible for expanding the scope of data used in models responsibly and effectively. You will build portable underwriting capabilities that can be adapted for different products, customer segments, and international markets. You will establish clear metrics and feedback loops to measure the business impact of your models. Leading the identification of opportunities to leverage transaction intelligence for credit-related applications will be a core focus. You will drive the standardization of model evaluation practices across the borrowing data science team. You will ensure that all machine learning initiatives align with regulatory expectations and internal risk policies. You will provide technical mentorship to junior data scientists and engineers within the borrowing function.

What you'll be working on

Your work will cover challenges such as improving underwriting models across various credit products. You will focus on expanding the data inputs available for modeling. You will lead initiatives to improve feature engineering and model deployment pipelines. You will enhance the use of transaction intelligence for credit-related applications. Developing underwriting capabilities for new customer segments and European markets will be a priority. You will shape Monzo's overall approach to advanced machine learning and artificial intelligence in borrowing. You will troubleshoot complex model performance issues in production environments. You will explore novel methodologies to reduce bias and increase fairness in credit decisioning.

Requirements

You possess hands-on experience with underwriting, pricing, limits, and lifecycle decisioning processes. You have a proven track record of improving performance across loans, Flex, and overdraft products. You understand how to expand data usage in models while managing risk responsibly. You have the capability to build portable models suitable for different markets and customer segments. You demonstrate strong ownership and the ability to drive projects forward without direct supervision. You are comfortable making decisions in environments with incomplete information and evolving priorities. You communicate complex technical concepts clearly to non-technical stakeholders. You have experience leading and developing a high-performing technical team.

Nice to have

Experience working with transaction intelligence within credit contexts is a significant advantage.

Skills & tools

Proficiency in Python and SQL is essential. Experience with feature stores, model training tools, and monitoring systems is required.

Practical notes

Please About the company

They'll be your partner and guide throughout the interview process. Initial Call (1 hour) You'll meet with one of our Senior Engineering Managers or Engineering Directors. They'll ask you about your previous experience, in particular people leadership, product delivery and technical leadership.