Machine Learning Scientist, Financial Crime

Our Machine Learning Scientists play a crucial role in our financial crime team, directly impacting Monzo's profitability by mitigating fraud and scams, which are often major cost drivers for banks. They ensure customer safety and significantly influence the overall customer experience. The tangible benefits of their work, whether for customers or the company, provide immense satisfaction.

Their responsibilities span various financial crime domains, including fraud detection and prevention, transaction monitoring for suspicious activities, customer risk assessment, and the development of operational tooling.

You'll play a key role by:This role sits as part of a multidisciplinary squad, collaborating with other Machine Learning Scientists, Data Scientists, Backend Engineers, Operations specialists, Product managers, and Risk managers. You'll play a key role by leveraging your deep experience of developing and deploying advanced Machine Learning models as to:

• 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.
• Design machine learning solutions that scale globally.

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., ??This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London)

?We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team.

??£1,000 learning budget each year to use on books, training courses and conferences.

??We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.

• You have a track record of deploying advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company.
• 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 passion for sharing knowledge and raising the technical bar across the team.
• You have a self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so.
• Using advanced ML techniques to ensure Monzo's customers money stays safe, even if their card, phone or account is compromised, 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 have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact.
• You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ambiguity.
• You have strong communication skills and are able to explain complex technical concepts to non-technical stakeholders
• You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and 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 in supporting your team in shaping the ML strategy of your area
• Experience working with financial crime, operations and in regulated institutions
• Commercial experience writing critical production code and working with microservices
• Experience in evaluating ML models in live environments such as through A/B tests