Senior Machine Learning Scientist – Borrowing

📍London, Cardiff or Remote (UK) | 💰 £70,000–£100,000 + Stock Options + Benefits

🚀 Join our mission to make money work for everyone

At Monzo, we’re challenging the outdated and complex world of traditional banking. Starting with a prepaid card, we’ve grown into a full-service financial platform—offering personal, joint, business, teen and children’s accounts, as well as credit cards, savings, investments, and pensions.

With iconic coral cards, innovative features like get-paid-early, engaging financial education, and award-winning customer service, we’ve become a trusted partner for millions.

But we’re not just here to build products. We’re here to solve problems and improve lives. ❤️
👉 Learn what it’s like to work at Monzo

About the Borrowing Team

Monzo’s borrowing products are core to our mission and sustainability. They meet vital customer needs while powering our ability to continue delivering world-class experiences. Our lending portfolio—from personal to business credit—is growing rapidly and expanding beyond the UK.

To accelerate this growth, we’re looking for brilliant, creative, and mission-driven individuals to help shape the future of borrowing at Monzo.

About the Role

As a Senior Machine Learning Scientist in our Borrowing Decision Science team, your mission is to improve outcomes for both customers and the business through better automated decisioning—driven by statistical modelling and machine learning.

We focus heavily on credit risk, but our work also informs utilisation, pricing, collections, and marketing strategies. You’ll join a small, expert team with established tooling to support the full lifecycle of ML models—from experimentation to deployment and monitoring.

You’ll own several high-impact ML applications end-to-end and be empowered to innovate with new data sources, methods, and tooling. You’ll collaborate across disciplines, with Engineers, Credit Strategy Analysts, Model Validation, and Product Managers, helping to define not just how we build models—but what problems we solve.

What You’ll Work On

• Design, develop, and deploy ML models that improve credit risk decisions and customer outcomes

• Own projects end-to-end: from experimental design, data curation, model training and evaluation, to deployment and ongoing monitoring

• Explore and apply cutting-edge techniques in ML and statistics to improve prediction accuracy and business performance

• Collaborate cross-functionally with Engineers, Analysts, and Product teams to integrate models into production systems and roadmaps

• Contribute to the strategic direction of our borrowing products and influence credit strategy beyond ML

Our Tech Stack

We use a modern, cloud-based tech stack to develop and scale our ML capabilities:

• Google Cloud Platform – primary analytics infrastructure

• BigQuery SQL & dbt – for data modeling and transformation

• PyData Stack (pandas, NumPy, scikit-learn, etc.) – model development and offline work

• Google AI Platform – cloud compute for training and tuning

• Python – for model microservices

• Go – for most other microservices

• AWS – backend and infra support

You Should Apply If You:

• Are results-driven and care deeply about impact on both customers and business outcomes

• Thrive in a fast-paced environment and enjoy a high level of ownership and autonomy

• Are excited to grow your skills across both business domains and advanced technologies

You’ll need to have:

• Strong SQL and Python skills, with solid engineering practices

• Deep understanding of machine learning and statistical models: e.g., logistic regression, gradient boosting, neural networks, survival analysis

• Strong grasp of statistical principles: hypothesis testing, confidence intervals, bootstrapping

• Hands-on experience building and maintaining ML models that drive business-critical decisions—ideally in a regulated environment

• Great attention to detail, while keeping the broader context in mind

• Excellent communication skills and the ability to collaborate with stakeholders from diverse backgrounds

• A collaborative and respectful approach that builds trust across teams

Nice to Have:

• Experience working in financial services or credit/lending environments

• Familiarity with real-time ML systems and model monitoring at scale

• Interest in shaping model validation frameworks and MLOps best practices

Interview Process

Our process is clear and transparent—no brainteasers or trick questions:

1. Initial call with a recruiter

2. Take-home task (flexible, designed to simulate real work)

3. Three virtual interviews:

   • Technical deep dive

   • Case study

   • Collaboration & values interview

We aim to complete the process in 3–4 weeks, depending on your availability. If you have any questions, contact us at tech-hiring@monzo.com.

👉 Read a team member’s detailed blog about the process here

What’s in it for you:

• 💰 £70,000–£100,000 base salary + stock options & benefits

• ✈️ Relocation support to the UK

• ✅ Visa sponsorship available

• 🏡 Work remotely across the UK (or in our London office with a hybrid option)

• 💻 MacBook and full home-working setup provided

• ⏰ Flexible hours – work when it suits you and your team

• 📚 £1,000 annual learning budget for books, training and conferences

• ➕ And much more – see our full list of benefits here

If you’re passionate about data, curious about human behaviour, and excited to shape the future of credit using cutting-edge ML—we’d love to hear from you.