Monzo
Lead Machine Learning Scientist, FinCrime
Vaga remota de Machine Learning Science com fit claro de localização do candidato.
Publicada10 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Reino Unido
Resumo da vaga
Lead Machine Learning Scientist, FinCrime
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
What you’ll be working on:
- Automatically and accurately detect suspicious user behaviours while minimising impact to genuine customers and operational costs
- Adapt quickly and appropriately to changing fraud and financial crime trends, ensuring our detection systems remain performant through time.
This will involve:
- Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.
- Leading the design and development of advanced real time Machine Learning models, for example exploring how neural network, graph-based, and sequence-based architectures can drive improvements in detection of financial crime.
- Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.
- 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.
You should apply if:
- You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
- You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact
- You're impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production
- You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
- Reducing financial crime and protecting customers with data driven strategies sounds exciting to you
- You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices
- You’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity
- You want to be involved in building a product that you (and the people you know) use every day
- You have a product mindset: you care about customer outcomes and you want to make data-informed decisions
- You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain
- You’re adaptable, curious and enjoy learning new technologies and ideas
Nice to haves:
- Experience working with financial crime and in regulated institutions
- Commercial experience writing critical production code and working with microservices
The interview process:
- 30 minute recruiter call
- 45 minute call with hiring manager
- 60 minute ML Modelling interview
- 60 minute Product & ML interview
- 60 minute behavioural interview
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