[Hiring] Staff Machine Learning Scientist, Financial Crime @Referrals Only

Role Description

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.

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.

Your day-to-day:

• Providing key technical leadership and shipping highly impactful ML-based solutions.
• Working across the FinCrime collective identifying the most impactful areas and leading solution development.
• Collaborating closely with product managers, data scientists, backend engineers, and designers in an agile environment.
• Advising senior business stakeholders and helping to set and advance our strategic direction in FinCrime.
• Steering technical work and driving up standards within the Machine Learning discipline.

This will involve:

• Identifying and scoping out the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.
• Leading advancements in our Financial Crime and Fraud detection capabilities, for example utilising deep learning, graph-based, and sequence-based architectures.
• Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline.
• Working closely with our MLOps team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.

Qualifications

• Multiple year track record of excellence leading the technical work of a team in the development and deployment of advanced Machine Learning models.
• Experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production.
• Experience in the domain of fraud, financial crime, security, or trust and safety.
• Experience in mentoring other ML practitioners, sharing knowledge and raising the technical bar across the team.
• Extensive experience writing production Python code and a strong command of SQL.
• Comfortable using Go lang, which is used in many of our backend microservices.
• Product mindset: care about customer outcomes and want to make data-informed decisions.
• Excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues.
• Adaptable, curious, and enjoy learning new technologies and ideas.

Requirements

• Impact driven and excited to own the end-to-end journey that starts with a business problem and ends with a measurable impact in production.
• Proactively identify the most impactful issues and opportunities and tackle them without being told to do so.
• Experience helping your team and stakeholders resolve ambiguity.
• Desire to be involved in building a product that you (and the people you know) use every day.

Benefits

• Relocation assistance to the UK.
• Visa sponsorship available.
• Flexible working hours and trust to work enough hours to do your job well.
• Learning budget of £1,000 a year for books, training courses, and conferences.
• Option to work part-time whenever possible to help meet other commitments or strike a great work-life balance.

Company Description

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, with a core value of protecting our users from being victims of financial crime.

The work we do results in directly measurable customer or company benefit, which is incredibly satisfying.