---
title: 'Staff Machine Learning Scientist, Financial Crime at Referrals Only'
canonical: 'https://feeny.ai/job/staff-machine-learning-scientist-financial-crime-referrals-only-london-aszbbpvh55jn'
type: 'job'
last_seen: '2026-09-14'
---

# Staff Machine Learning Scientist, Financial Crime at Referrals Only

- **Company:** Referrals Only
- **Location:** London, United Kingdom
- **Work type:** remote
- **Posted:** 2024-03-12
- **Last confirmed live:** 2026-09-14
- **Apply:** https://job-boards.greenhouse.io/monzoreferrals/jobs/5774781

## Job description

📍London, or Remote UK  | Salary £140-£175,000 + stocks + [benefits](https://monzo.com/careers#benefits) | [Hear from the team](https://www.youtube.com/watch?v=U62l09nB0M4) ✨

About our Machine Learning, Financial Crime Team:

Our Financial Crime Data team consists of over 25 people across 4 data specialisms: Analytics Engineers, Data Analysts, Machine Learning Scientists and Data Scientists.

Our financial crime team has a huge impact on Monzo. A core value for us is protecting our users from being victims of financial crime. Stopping fraud protects our users and is one of the largest cost lines in a bank's P&L. We have a major influence on the overall customer experience and it’s our duty to keep our customers safe. The work we do results in directly measurable customer or company benefit, which is incredibly satisfying.

Our Machine Learning Scientists work on a range of problems within the different financial crime areas ranging from fraud detection and prevention, transaction monitoring for different types of suspicious activity through to customer risk assessment and operational tooling.

What you’ll be working on:

As a Staff ML Scientist, you’ll be the most senior Individual Contributor (IC) Machine Learning Scientist across the entire FinCrime collective! This will give you a real opportunity to lead us into an exciting new phase of fraud and financial crime prevention, utilising billions of rows of data and the learnings from your previous successes in designing and building advanced Machine Learning based real time detection systems.

We’re talking about Deep Learning, Graph neural networks, transformers – you’ll have space to design the architecture that will help us take our real time detection systems to the next level.

More specifically, we’ll be expecting you to leverage your deep experience of developing and deploying advanced Machine Learning models within the fields of financial crime, fraud, security, or trust and safety to:

- Lead our ongoing journey to build an advanced, scalable, extensible, automated fraud and FinCrime detection system that effectively prevents crime while minimising impact to genuine customers and operational costs.
- Ensure our detection systems can adapt quickly and appropriately to changing fraud and financial crime trends, remaining performant through time.

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.

## Your day-to-day

As our most senior technical IC, you’ll be providing key technical leadership and shipping highly impactful ML-based solutions. You’ll be empowered to work across the FinCrime collective identifying the most impactful areas and leading solution development.

You’ll work with our mission-oriented cross functional product squads, collaborating closely with product managers, data scientists, backend engineers and designers in an agile environment.

You’ll be expected to use your technical expertise to advise senior business stakeholders and help to set and advance our strategic direction in FinCrime.

You’ll also be a technical leader within the Machine Learning discipline, helping to steer technical work and drive up standards.

This will involve:

- Working with stakeholders across the organisation to identify and scope out the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.
- Bringing the learnings from your previous successes in designing and building advanced Machine Learning based real time detection systems to lead advancements in our Financial Crime and Fraud detection capabilities, for example utilising deep learning, graph-based, and sequence-based architectures.
- 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:

What we’re doing here at Monzo excites you!

- You have a multiple year track record of excellence leading the technical work of a team in the development and deployment of advanced Machine Learning models tackling 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 in the domain of fraud, financial crime, security or trust and safety.
- 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 experience in, and a passion for, mentoring other ML practitioners, 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 tackle them without being told to do so
- Using advanced machine learning techniques to minimise financial crime and protect customers from fraud 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](https://go.dev/) 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

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
- 4 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 tech-hiring@monzo.com. Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason.

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](https://monzo.com/careers/)

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.

## #LI-REMOTE #LI-NJ1

## About Referrals Only

## Company Overview
- **One-liner**: Marqeta is the world’s first modern card issuing platform, providing open APIs that enable businesses to create, manage, and scale customized payment card programs.
- **Entity Type**: Public (Ticker: MQ on NASDAQ)
- **Headquarters**: Oakland, California, USA
- **Founded**: 2010
- **Founders**: Jason Gardner (Founder & Executive Chairman)

## Core Business
- **Primary industry**: Financial Technology (Fintech) — Modern Card Issuing & Payment Solutions
- **Target customers**: B2B; serves a wide range of industries including digital banking, on-demand delivery, buy now, pay later, expense management, retail, and workforce payments. Customers include Square, DoorDash, and other high-growth fintech and enterprise companies.
- **Mission or purpose statement**: To simplify payments and enable any company to deliver delightful payment experiences natively, powering more flexible, engaging, and innovative payment products.

## Products & Services
- **Modern Card Issuing Platform (SaaS/API)**: Fully open API platform that allows developers to launch new credit and debit card programs with speed, flexibility, and scale. Supports instant wage access, embedded finance, and custom card products.
- **Compliance & Risk Management (Service)**: Integrated fraud detection, spend control, and compliance tools to ensure high levels of security and uptime.
- **Global Expansion Capabilities (Platform)**: Certified to operate in over 40 countries across the US, Europe, and Asia, enabling businesses to scale globally.

## Market Standing
- **Valuation/Market Cap**: As a public company, market cap fluctuates. As of mid-2026, Marqeta is a publicly traded company valued in the multi-billion dollar range (exact figure varies with market conditions).
- **Key Metric**: Annual Revenue — $383 billion+ in total volume processed in 2025; 80x volume growth since 2017; 99.99% platform uptime in 2025.
- **Notable Investors/Partners**: Key customers include Square (Block), DoorDash, and other leading fintech and enterprise firms. Partners include issuing banks, networks (e.g., Visa, Mastercard), and card fulfillment providers.
- **Growth Signals**: Recognized as a CNBC Disruptor (top 50 in 2021 award); consistent expansion into new geographies (EU, UK, Asia); continued hiring across multiple departments and regions (US, Canada, UK).

## Competitive Advantages
- **First-mover & category leader**: Marqeta defined the modern card issuing category with its open API platform, giving it a decade-plus head start over competitors.
- **Scalability & reliability**: Proven track record of 99.99% uptime and handling massive transaction volumes (80x growth since 2017) — critical for enterprise customers.
- **Deep integration with major networks**: Pre-existing relationships with Visa, Mastercard, and issuing banks shorten time-to-market for customers.
- **Developer-first approach**: Open APIs and developer tools make it easy for engineering teams to build custom payment experiences quickly.

## Strategic Focus
- **Global expansion**: Continuing to expand its certified operations into new countries (currently 40+) to serve multinational customers.
- **Embedded finance & new use cases**: Driving adoption in instant wage access, embedded finance, and enterprise expense management.
- **AI & automation**: Investing in AI-powered fraud detection, risk management, and product automation (e.g., hiring for Principal Security Engineer, Product & AI; Lead Product Manager, Enterprise AI & Automation).
- **Platform stability & security**: Maintaining industry-leading uptime and security compliance as core differentiators.

## Why Work Here
- **Culture & values**: Marqeta emphasizes a culture of “Simplify and Innovate,” “Solve for the Customer,” “Do What’s Right,” “Make it Count,” and “Win as a Team.” Employee Resource Groups (ERGs) include BlackCard, HOLA, RepresentAsian, Desi, MQ-Proud, Vets@MQ, Women’s Group, Parents’ Group, and Marqetaglots.
- **Remote/hybrid policy**: Many roles are remote (US, Canada, UK), with some positions based in Oakland, CA or London, UK. The company supports flexible work arrangements.
- **Notable perks & engineering culture**: Fast-paced, purpose-driven environment; strong focus on developer experience and open APIs; opportunities to work on cutting-edge payment infrastructure at massive scale. The company invests heavily in early career talent and internal mobility.
- **Award-winning workplace**: Recognized as a top workplace (e.g., CNBC Disruptor) and offers a collaborative, inclusive environment.

## Sources
1. [Marqeta About Us](https://www.marqeta.com/company/about-us)
2. [Marqeta Careers Page](https://www.marqeta.com/company/careers)
3. [Marqeta Homepage](https://www.marqeta.com/)
4. [Greenhouse Job Board](http://job-boards.greenhouse.io/marqeta)
5. [MQ Referrals Job Board](https://job-boards.greenhouse.io/mqreferrals/jobs/7743043)

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