National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Product Manager, Fincrime Efficiency

Monzo
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist, Growth Marketing...

Senior Data Scientist, Growth Marketing

Senior Data Engineer

Data Engineering Product Owner

Data Engineering Product Owner

Senior Data Science Manager

We’re on a mission to make money work for everyone.

We’re waving goodbye to the complicated and confusing ways of traditional banking.

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 the role

We are looking for a Senior Product Manager to lead our efforts in improving the efficiency and effectiveness of our Financial Crime (Fincrime) Operation teams.

Your mission is to build and provide world class tech-led toolings, through more automation, usage of GenAI, and process redesign, to empower our (Fincrime) Investigators and help Monzo achieve scalable and sustainable growth. You’ll drive efficiency gains, while maintaining or improving decision quality, and ensuring a seamless customer experience.

What You’ll Be Working On:

  • Optimising Fincrime Investigation Workflows: Reduce handling time while maintaining or improving decision accuracy, particularly for high-effort tasks.
  • Scaling Automation & AI-first Solutions: Drive towards 100% automation where human intervention is only required in complex cases or when necessary for customer experience.
  • Enhancing Tooling for COps (Customer Operations): Improve existing tools and build new solutions to reduce manual efforts, increase efficiency, and streamline investigations.
  • Improving Demand Forecasting & Workforce Planning: Enhance forecasting capabilities to support central Workforce Management (WFM), optimizing capacity planning and scheduling to drive cost savings and improve customer experience.
  • Driving Cultural & Process Improvements: Improve investigator incentives, skills leveling, and training to create a more efficient and high-performing team.

Your day to day work:

  • Lead a 10+ cross functional squad, across risk, engineering, data, machine learning, and operation to develop and deliver on the strategic product roadmap.
  • Identify opportunities for efficiency improvements without compromising quality of decision & customer experience.
  • Build new toolings and/or improvements to existing toolings to help COps improve their efficiency.
  • Collaborate closely with our Ops Collective to deliver improvements to forecasting & planning.
  • Act as the central point of execution for our strategy/ vision to move towards building AI-first solutions.

You should apply if:

  • Proven experience in product management, ideally within fintech or scale up companies.
  • Strong understanding of automation, AI-driven tooling, and operational efficiency improvements.
  • Experience working with cross functional teams, especially operational teams to deliver impactful solutions.
  • Ability to make decisions balancing difficult trade offs.
  • A data-driven mindset, with experience using insights to drive product decisions and measure success.

The interview process:

Our interview process involves 4 main stages:

  • Recruiter Call
  • Initial Call with Hiring Manager
  • Interview Loop, consisting of three 1 hour long interviews (Project Walkthrough, Case Study and Leadership)
  • Final Interview

This process should take around 3-4 weeks - your schedule is really important to us, so we promise to be as flexible as possible!

You’ll hear from us throughout the application process, but if you’ve got any questions, please reach out to .

We’ll only close this role once we have enough applications for the next stage. Please submit your application as soon as possible to make sure you don’t miss out.

What’s in it for you:

£95,000 - 125,000 share options.

We’ll help you relocate to the UK.

We can sponsor your visa.

This role can be based in our London office, but were open to distributed working within the UK.

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.

Plus lots more!

Equal opportunities for everyone

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.

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 dont need full or birth names at application stage.

J-18808-Ljbffr

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.