Staff Machine Learning Scientist - Financial Crime

4d4 days ago

Monzo Bank

London, GB · Full-time · £140,000 – £175,000

About this role

As the most senior Individual Contributor Machine Learning Scientist across the FinCrime collective, you will lead advancements in fraud and financial crime prevention. You will utilise billions of rows of data and your experience designing advanced real time detection systems to shape the next phase of work at Monzo.

Your day-to-day involves providing technical leadership while shipping highly impactful ML-based solutions. You will identify the most impactful opportunities across the collective and lead solution development in collaboration with product managers, data scientists, backend engineers and designers.

The Financial Crime Data team comprises over 25 people across Analytics Engineers, Data Analysts, Machine Learning Scientists and Data Scientists. The work directly protects users from fraud, reduces one of the largest cost lines in the bank’s P&L and delivers measurable customer and company benefit.

You will have space to design architectures using Deep Learning, Graph neural networks and transformers. The role offers the opportunity to justify and demonstrate effectiveness while steering technical standards and setting strategic direction in financial crime detection.

Requirements

Deep experience developing and deploying advanced Machine Learning models within financial crime, fraud, security, or trust and safety.
Proven success designing and building advanced Machine Learning based real time detection systems.
Strong expertise with Deep Learning, Graph neural networks and transformers for production systems.
Ability to justify and demonstrate effectiveness of technical approaches against business and customer needs.
Experience leading technical work and raising standards within a Machine Learning discipline.

Responsibilities

Lead the ongoing journey to build an advanced, scalable, extensible, automated fraud and FinCrime detection system that prevents crime while minimising impact to genuine customers.
Ensure detection systems adapt quickly to changing fraud and financial crime trends while remaining performant through time.
Work with stakeholders across the organisation to identify and scope the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.
Provide key technical leadership and ship highly impactful ML-based solutions across the FinCrime collective.
Advise senior business stakeholders and help set and advance strategic direction in FinCrime.
Steer technical work within the Machine Learning discipline and drive up standards across the team.