Staff Machine Learning Scientist, Financial Crime

About this role

📍London, or Remote UK | Salary £140-£175,000 + stocks + benefits | Hear from the team ✨ About our Machine Learning, Financial Crime Team: Our Financial Crime Data team consists of over 25 people across 4 data specialisms: Analytics Engineers, Data Analysts, Machine Learning Scientists and Data Scientists. Our financial crime team has a huge impact on Monzo. A core value for us is protecting our users from being victims of financial crime.

Stopping fraud protects our users and is one of the largest cost lines in a bank's P&L. We have a major influence on the overall customer experience and it’s our duty to keep our customers safe. The work we do results in directly measurable customer or company benefit, which is incredibly satisfying. Our Machine Learning Scientists work on a range of problems within the different financial crime areas ranging from fraud detection and prevention, transaction monitoring for different types of suspicious activity through to customer risk assessment and operational tooling.

What you’ll be working on: As a Staff ML Scientist, you’ll be the most senior Individual Contributor (IC) Machine Learning Scientist across the entire FinCrime collective! This will give you a real opportunity to lead us into an exciting new phase of fraud and financial crime prevention, utilising billions of rows of data and the learnings from your previous successes in designing and building advanced Machine Learning based real time detection systems.

We’re talking about Deep Learning, Graph neural networks, transformers – you’ll have space to design the architecture that will help us take our real time detection systems to the next level. More specifically, we’ll be expecting you to leverage your deep experience of developing and deploying advanced Machine Learning models within the fields of financial crime, fraud, security, or trust and safety to: Lead our ongoing journey to build an advanced, scalable, extensible, automated fraud and FinCrime detection system that effectively prevents crime while minimising impact to genuine customers and operational costs.

Ensure our detection systems can adapt quickly and appropriately to changing fraud and financial crime trends, remaining performant through time. The technical approaches you take to solve these problems will be very much in your hands and we’ll strongly encourage and support experimentation and innovation. We’ll be expecting you to justify and demonstrate effectiveness along the way, making sure the approach meets our business and customer needs.