Data Science Manager, Financial Crime

We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award-winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo.

About our Financial Crime Data Team: As we continue to scale, we’re looking for a Data Science Manager to lead one of our key product areas for Financial Crime. As a Data Science Manager, you’ll be working in an ever-changing environment in collaboration with Product, Risk and Engineering peers and champion the data strategy and lead a cross-functional team. You’ll help us build and improve these for now and for our future roadmap. We’re looking for a leader with hands-on experience, a data-driven strategic leader who can bring fresh thinking and new ways to inspire the team and our customers.

What you’ll be working on:

• You’ll work closely with the Product Managers, engineers, and Financial Crime control owners in an agile product environment.
• You’ll champion the use of data, bringing ideas to life through a rigorous analytical approach.
• Your work will focus on improving our efforts in financial crime detection, prevention and mitigation, ensuring we stay ahead of emerging threats and regulatory requirements.
• You’ll help your team grow, hiring new team members and supporting their personal development.
• You will manage a team with Data Scientists and Data Analysts, working together with Analytics Engineers to drive product innovation.

You should apply if:

• What we’re doing here at Monzo excites you!
• You must have at least 4 years of experience as a Data Science Manager - at least 2 of them managing a data team larger than 4 people.
• You are a strong strategic data leader and love to drive decisions.
• Strong experience with working with executive or C-level peers, managing stakeholders across levels of seniorities and disciplines.
• You know what it takes to manage top-tier Data talent.
• You’re excited by the opportunity to work autonomously to impact the future of a fast-growing, ever-evolving business.
• You’re familiar with using a variety of Data Science tools (from business intelligence, experimentation and causal inference through to machine learning), and coding languages (Python and SQL).
• You know when to pick the right tool, and can help others do the same.
• Experience in financial crime, fraud detection, or similar areas (Trust & Safety, Integrity, Security) is a plus.

The Interview Process: Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!

• 30 minute recruiter call
• 45 minute call with hiring manager
• 3 x 1-hour video calls with various team members

What’s in it for you:

• We can help you relocate to the UK.
• We can sponsor visas.
• 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, at times that suit you and your team.
• Learning budget of £1,000 a year for books, training courses and conferences.

Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone.