At a Glance
- Tasks: Lead the development of advanced ML systems to combat financial crime and fraud.
- Company: Join Monzo, a forward-thinking tech company dedicated to user safety.
- Benefits: Competitive salary, stocks, flexible hours, and a £1,000 learning budget.
- Other info: Remote work options available, with opportunities for career growth.
- Why this job: Make a real impact in protecting customers from financial crime using cutting-edge technology.
- Qualifications: Proven experience in ML model development and a passion for mentoring others.
The predicted salary is between 140000 - 175000 £ per year.
📍London, or Remote UK | Salary £140-£175,000 + stocks + benefits
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 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
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.
Staff Machine Learning Scientist, Financial Crime in London employer: Referrals Only
Monzo is an exceptional employer that prioritises the well-being and growth of its employees, offering a dynamic work culture where innovation thrives. With a strong focus on protecting customers from financial crime, our Staff Machine Learning Scientists play a pivotal role in shaping impactful solutions while enjoying flexible working hours, a generous learning budget, and opportunities for professional development. Whether based in our vibrant London office or working remotely across the UK, you'll be part of a mission-driven team dedicated to making a real difference in the banking sector.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Scientist, Financial Crime in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Monzo. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for your interviews by diving deep into financial crime trends and machine learning techniques. Show us you’re not just a tech whiz but also passionate about making a real impact!
✨Tip Number 3
Practice your storytelling skills. When discussing your past projects, focus on the challenges you faced and how you overcame them. We love hearing about your journey and the results you achieved!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we’re always looking for passionate candidates who want to join our mission.
We think you need these skills to ace Staff Machine Learning Scientist, Financial Crime in London
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for tackling financial crime shine through! We want to see how excited you are about using machine learning to make a real difference in people's lives.
Tailor Your Experience:Make sure to highlight your relevant experience in developing and deploying advanced ML models. We’re looking for specific examples that demonstrate your impact in the field of fraud detection and financial crime.
Be Clear and Concise:Keep your application straightforward and to the point. Use clear language to explain your achievements and how they relate to the role. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Referrals Only
✨Know Your Stuff
Make sure you brush up on your knowledge of advanced Machine Learning techniques, especially in the context of financial crime. Be ready to discuss your previous projects and how they relate to fraud detection and prevention. This will show that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Leadership Skills
As a Staff ML Scientist, you'll be expected to lead and mentor others. Prepare examples of how you've successfully led teams or projects in the past. Highlight your ability to drive technical excellence and how you’ve helped elevate the skills of your colleagues.
✨Understand the Business Impact
Be prepared to discuss how your work has had a measurable impact on business outcomes. Think about specific metrics or results from your previous roles that demonstrate your ability to tackle real business problems with your Machine Learning solutions.
✨Ask Insightful Questions
During the interview, don’t hesitate to ask questions that show your interest in the role and the company. Inquire about the challenges the team is currently facing in financial crime detection or how they measure success in their projects. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
