Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Science Manager, Financial Crime

Monzo
City of London
2 days ago
Create job alert
Overview

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 us: We’re here to make money work for everyone and we're doing things differently. For too long, banking has been obtuse, complex and opaque. We want to change that and build a bank with everyone, for everyone. Our amazing community suggests features, test the app and give us constant feedback so we can build something everyone loves. We're focused on solving problems, rather than selling financial products. We want to make the world a better place and change people's 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, collaborating 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, data driven strategic leader who can bring fresh thinking and new ways to inspire the team and our customers.

Your day-to-day

  • Be a key leader in building a discipline of exceptional data scientists and analysts working on making Monzo world class at detecting and fighting financial crime activity
  • Help hire, develop and retain talented data people
  • Generate insights that can change the direction of our financial crime strategy
  • Bring data leadership and rigour to our approach to product development and build a strategic understanding of the business while structuring complex projects to bring them to life
  • Liaise with risk, product and engineering managers to keep making sure we collect the right data to produce relevant business insights
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

Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on

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

And much more, see our full list of benefits here

#LI-NB2 #LI-Remote

Equal opportunities

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. You can read more in our blog, 2024 Diversity and Inclusion Report and 2024 Gender Pay Gap Report.

We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

If you have a preferred name, please use it to apply. We don\'t need full or birth names at application stage


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Manager, Operations Cardiff, London or Remote (UK)

Transaction Monitoring Data Analyst

Transaction Monitoring Data Analyst

Senior Data Science Strategist - Featurespace

Data Analyst

Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.