At a Glance
- Tasks: Join us to enhance customer experiences through innovative machine learning solutions.
- Company: Be part of Monzo, a forward-thinking bank transforming finance for everyone.
- Benefits: Competitive salary, stock options, flexible hours, and a £1,000 learning budget.
- Why this job: Make a real impact in the financial world with cutting-edge technology and a supportive team.
- Qualifications: Strong SQL and Python skills, plus experience in machine learning model development.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
The predicted salary is between 74000 - 90000 £ per year.
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.
At Monzo we want to make money work for everyone. We care deeply about our 15+ million customers. Through magically simple products and actionable insights, we put our customers in control of their finance. Our products are different by design, and reliable at our core. Our range of borrowing products are critical to Monzo’s mission. Not only do they serve important needs of our customers, they are also a key revenue driver to support Monzo keep delivering great products and experience. We have seen stellar growth and deep engagement with millions of borrowers, supported by effective and efficient credit risk management. Our product portfolios are still expanding fast, from personal to business credit, and markets beyond UK.
The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing. You will be working alongside a team of very experienced and highly efficient ML Scientists, with well established toolings for the fully lifecycle of ML models. Each of you owns multiple ML applications end-to-end, from experiment design and data curation, to deployment and monitoring. You will be empowered to innovate in the data, methodologies and toolings, so we can build better models easier and faster. You will have exposure to all Borrowing products and applications, with autonomy to decide what are the most impactful topics to work on, and how to deliver them. You will work closely with our Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers, to fit your model development into the product roadmap. You are also empowered to think big about the business, market and customers, to influence our product and credit strategy beyond just the world of models.
Our technology stack:
- Google Cloud Platform for all of our analytics usages
- BigQuery SQL and dbt for our data modelling and warehousing
- PyData stack for model development and offline deployment
- Google Vertex AI platform for cloud computing
- AWS for backend infrastructure
- Python for ML model microservices
- Go lang for most other microservices
- AI toolings for productivity
- Google suites including access to Gemini ChatGPT enterprise Claude code
You Should Apply If:
- You are result oriented and motivated by the impact on our customers and business
- You enjoy a high degree of autonomy and thrive in a fast‑paced environment
- You are keen to grow your knowledge in both business and technology
You Must Have:
- Excellent SQL and Python skills with good understanding of best practices in software engineering and data engineering
- In‑depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc
- Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap
- Experience of end‑to‑end model development and maintenance of ML models used for business critical automated decisioning, in a consumer facing industry
- Great attention to details while keeping an eye on the big picture
- Excellent communication skills to articulate complex problems
- Capability to build mutual respect and trust with people of different background
Nice To Have:
- Experience in UK/EU retail lending businesses for personal/business customers
- Experience of ML model governance in a regulated industry
- Experience in leverage modern day AI tools for productivity
The Interview Process:
- 30’ Recruiter Call
- 45’ Initial Call
- 60’ ML technical skill interview
- 60’ Behavioural interview
All interviews will be conducted through Google Meet. 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.
What’s In It For You:
- £86,000 to £105,000 + stock options & benefits
- Help to relocate to the UK
- Sponsor visas
- Role can be based in London office with hybrid working pattern, or fully remote within UK with occasional travels to London
- 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
- Flexible working hours, 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.
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. This is integral to our mission of making money work for everyone. 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.
Senior Machine Learning Scientist, Borrowing in London employer: Monzo Bank
Contact Detail:
Monzo Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Scientist, Borrowing in London
✨Tip Number 1
Get to know Monzo's mission and values inside out. When you’re chatting with the team, show them you’re not just another candidate – you’re genuinely excited about making money work for everyone. This passion can really set you apart!
✨Tip Number 2
Prepare for your interviews by brushing up on your SQL and Python skills. Make sure you can talk through your past projects and how they relate to credit risk modelling. We want to see your thought process and how you tackle challenges!
✨Tip Number 3
Don’t shy away from asking questions during your interviews. It shows you’re engaged and interested in the role. Ask about the team dynamics, the tools they use, or how they measure success. This is your chance to find out if Monzo is the right fit for you too!
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re proactive and keen to join the Monzo family. Let’s make magic happen together!
We think you need these skills to ace Senior Machine Learning Scientist, Borrowing in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Machine Learning Scientist role. Highlight your experience with SQL, Python, and machine learning models that align with our mission at Monzo. We want to see how your skills can help us make money work for everyone!
Showcase Your Impact: When detailing your past experiences, focus on the impact you've made in previous roles. Use specific examples of how your work improved customer outcomes or business processes. We love seeing results-oriented candidates who are motivated by making a difference!
Be Clear and Concise: Keep your application clear and to the point. Avoid jargon and ensure your communication is easy to understand. We appreciate candidates who can articulate complex problems simply, as this reflects the kind of collaboration we value at Monzo.
Apply Through Our Website: We encourage you to apply directly through our website. This way, you’ll ensure your application gets to the right people quickly. Plus, it’s the best way to stay updated on your application status. We can’t wait to hear from you!
How to prepare for a job interview at Monzo Bank
✨Know Your Stuff
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss your experience with statistical and machine learning models, especially those mentioned in the job description like gradient boosted trees and logistic regression. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to articulate complex problems you've tackled in the past. Think about how you approached these challenges and the impact your solutions had on the business. This will demonstrate your ability to think critically and creatively, which is key for a Senior Machine Learning Scientist.
✨Understand the Business
Familiarise yourself with Monzo's mission and product offerings. Think about how your role as a Machine Learning Scientist can contribute to improving customer outcomes and driving business growth. Showing that you understand the bigger picture will impress the interviewers.
✨Communicate Effectively
Practice explaining your technical knowledge in simple terms. You’ll be working closely with various teams, so being able to communicate complex ideas clearly is crucial. Prepare some examples of how you've successfully collaborated with others in the past to build mutual respect and trust.