Staff Machine Learning Scientist, Financial Crime

monzoreferrals; United States; Hybrid; USD 185,000 - 231,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation support

£1,000 learning budget

Job summary

monzoreferrals is seeking a senior individual-contributor to lead the technical direction of ML-driven financial crime and fraud prevention at scale. You will operate within a cross-functional data org and influence real-time detection systems that protect customers while reducing costs.

You will architect scalable detection platforms, ship real-time ML models, and mentor practitioners while collaborating with MLOps.

Qualifications

• Multiyear senior leadership of ML teams with production impact.
• Hands-on experience designing and deploying ML systems for financial crime, fraud, security, or trust and safety.
• Expertise in real-time detection using deep learning, graph neural networks, or transformers.
• Proficiency in Python and SQL; willingness to learn Go for backend microservices.
• Ability to mentor and raise technical standards across a team.

Responsibilities

• Architect and advance a scalable, automated detection platform for fraud, transaction monitoring, and customer risk assessment.
• Design and ship real-time ML models using DL, graph-based, and sequence-based approaches for production environments.
• Identify high-impact opportunities across the financial crime domain and lead end-to-end solution development.
• Advise senior stakeholders and contribute to the long-term fraud prevention strategy.
• Mentor ML practitioners and raise the technical bar across the discipline through example and knowledge sharing.
• Partner with MLOps to evolve tooling for rapid iteration and model lifecycle optimization.

Skills

Senior ML leadership

ML systems design

Python

SQL

Go (learning)

Deep learning

Graph neural networks

Transformers

ML Ops tooling

Tools

MLOps tooling

Job description

Role overview

A senior individual-contributor opportunity leading the technical direction of machine-learning based financial crime and fraud prevention at scale. The role sits within a cross-functional data organisation of 25+ practitioners spanning analytics engineering, data analysis, and ML, with a mandate to evolve real-time detection systems that protect customers while reducing operational cost.

Responsibilities

• Architect and advance a scalable, extensible, automated detection platform covering fraud, transaction monitoring, and customer risk assessment.
• Design and ship real-time ML models using deep learning, graph-based, and sequence-based approaches for production environments.
• Identify the highest-impact opportunities across the financial crime collective and lead solution development end-to-end.
• Advise senior business stakeholders and contribute to long-term strategy for fraud and financial-crime prevention.
• Mentor ML practitioners and raise the technical bar across the discipline through example and knowledge sharing.
• Partner with MLOps to evolve tooling that supports rapid iteration and optimisation of the full model lifecycle.

Requirements

• Several years of senior experience leading the technical work of ML teams, with measurable production impact.
• Hands-on background designing and deploying advanced ML systems in financial crime, fraud, security, or trust and safety.
• Deep expertise in deep learning, graph neural networks, transformers, or comparable architectures for real-time detection.
• Strong, daily production-level proficiency in Python and SQL, with willingness to learn Go for backend microservices.
• A self-starter mindset that proactively surfaces and tackles the most impactful problems.
• Comfort navigating ambiguity and helping stakeholders and teammates resolve it.

Benefits and work setup

• Salary range £140,000–£175,000 plus equity and benefits.
• Hybrid working from a London office or fully remote within the UK, with ad hoc London meetups.
• Flexible hours, part-time considered, and a £1,000 annual learning budget for books, courses, and conferences.
• Visa sponsorship and relocation support available.