🚀 Our mission is to make money work for everyone.

We say goodbye to the complicated and confusing way of traditional banking.

With our brightly colored cards and the ability to get paid early, 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’re about solving problems and changing lives through Monzo ❤️

Hear from our team what it’s like to work at Monzo ✨

📍London or remote UK | 💰 £130-155k + benefits | Hear from the team ✨

⭐ Our Fincrime Machine Learning Team

Fincrime Machine Learning is the largest ML team within Monzo: our mission is to develop financial crime defence systems to protect Monzo and our customers.

At Monzo, Machine Learning Scientists are responsible for the entire ML lifecycle, from formulating ML problems to deploying models and monitoring their impact on key product and business metrics.

Our work in Fincrime has a direct, measurable impact on both customers and the business. We have a duty to keep customers safe and financial crime prevention has a strong impact on the customer experience. Furthermore, preventing financial crime is crucial to Monzo’s bottom line, as fraud and scams are typically among the largest costs to a bank’s profit and loss account.

Our Machine Learning scientists work together in cross-functional teams across Data, Engineering, Product and Risk. They tackle a wide range of problems including fraud detection and prevention, transaction monitoring for various suspicious activities, customer risk assessment and operational tools.

🔑You play a key role by…

• You will lead machine learning across the financial crime domain at Monzo, helping us develop the vision, strategy and team of machine learning experts for this area.
• You will collaborate with interdisciplinary teams, product managers, engineers and other data colleagues (data analysts, data scientists, analytics engineers) to ensure we capture the most impactful machine learning opportunities and address them with pragmatic, iterative and high-quality systems.
• You will lead the design, build, and delivery of machine learning systems. You will work at the intersection of data, product, and engineering, ensuring that all systems we build are secure and properly validated.
• You will support, coach and develop high-performing Machine Learning Scientists through regular 1:1 conversations, continuous feedback and cultivating relationships with other leaders at Monzo.
• As the leader of the largest ML team at Monzo, you will work collaboratively with other Machine Learning and Platform teams to ensure that Machine Learning at Monzo adheres to industry best practice and uses the best tools to achieve high performance and maintain high productivity.

• You contribute to best practices: you help us become an exceptional workplace for ambitious, highly motivated people.
• You will play a key role in growing the impact of machine learning within Monzo. You will empower machine learning scientists to work on the full lifecycle of their models, including deploying the models they train into production. You will also contribute to how we define and build our workflows and tools as we scale our field.

You must submit an application if

• You have experience leading teams of 5 or more high-performing Machine Learning professionals and own Machine Learning systems in production.
• You understand how ML systems work, how they should be designed based on the business problem they solve, and you can communicate this to technical and non-technical people.
• You have experience working with senior business stakeholders and product teams to implement ML systems.
• You know what makes a high performing team and how to achieve it. You care deeply about helping others achieve their goals and become the best Machine Learning Scientists they can be.
• You have an empathetic leadership style and you build strong, effective relationships.

🙌What’s in it for you?

💰£130 – 155,000 ➕stock options

✈️ We help you with your move to the United Kingdom

✅ We can sponsor your visa

📍This role can be based in our London or Cardiff offices, however we are open to distributed working within the UK (with ad-hoc meetings in London)

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

📚£1,000 learning budget per year, to spend on books, training and conferences.

🏡We make sure you can work from home. All employees get a Macbook and for employees who work completely remotely, we offer extra support for the home work setup.

➕ And much more! Read our full list of benefits.

🌈 The application process consists of 3 important steps:

• Recruitment call
• 45 minute interview with the hiring manager
• 4 x 1 hour interviews with different team members

Our average process takes around 2-3 weeks, but we always work around your availability. You’ll have the chance to speak to our recruitment team at various points during your process, but if you have any specific questions before then, please contact us at [email protected]. Please also use that email address to let us know if there’s anything we can do to make your application process easier for you, whether because of disability, neurodiversity or any other personal reason.

Equal opportunities for everyone

Diversity and inclusion are a priority for us and we ensure we have strong support for all our people to thrive at Monzo. At Monzo, we embrace diversity by creating an inclusive environment where all people can do the best work of their lives with us. This is integral to our mission to make money work for everyone. You can read more in our blog, 2023 Diversity and Inclusion Report and 2023 Gender Pay Gap Report.

We are an equal opportunity employer. All applicants will receive consideration for employment without regard to age, ethnicity, religion, gender, sexual orientation, gender identity, family or parental status, national origin, veteran status, neurodiversity, or disability status.

If you have a preferred name, please use that to sign up. We don’t require full or birth names in the sign up phase 😊

Originally posted on Himalaya