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About the Role
This role is part of the fast-growing Borrowing business at Monzo, focusing on building simple, transparent ways for customers to borrow with confidence. You will join a collaborative team, own meaningful work, solve real problems with data, and ship improvements that enhance the borrowing experience. The two-year scheme involves three eight-month rotations, offering broad exposure to modern credit and helping you discover your strengths.
Responsibilities
- Own meaningful work from day one.
- Solve real problems with data.
- Ship improvements that make borrowing better for customers.
- Build technical skills.
- Learn from experienced mentors.
- Work on projects with real business and customer impact.
- See your work make it into production.
- Help shape the lending products customers use.
- Help answer key questions like who we lend to, how much, and how to help more customers access credit responsibly.
- Use data, experimentation, and commercial thinking to turn answers into action.
- Develop and improve models that power lending decisions.
- Use machine learning and statistical techniques to create better customer outcomes.
- Build and maintain models to understand future credit losses, manage capital, and support growth.
- Provide independent review and challenge of lending strategies and models.
- Ensure decisions remain robust, well-governed, and customer-focused.
Requirements
- Graduated in 2026 or graduating in 2027 with, or expecting to achieve, at least a 2:1 in a STEM, Economics or another highly analytical degree.
- Enjoy solving complex problems using data.
- Curious, collaborative, and excited to learn new technologies.
- Enjoy asking questions, digging into data, and finding better ways to solve problems.
- Want to build products that genuinely improve customers' financial lives.
- Have the full right to work in the UK with no limitations.
- Able to work from our London office three days per week on a hybrid basis.
Skills
- STEM
- Economics
- Analytical
- Data analysis
- Machine learning
- Statistical techniques
- Commercial thinking
- Programming languages like SQL & Python
- Effective communication
- Presenting data analysis
Location
- London
Work Type
- Hybrid (3 days per week in the office)
- Flexible working hours
Experience Level
- Graduate
Education Level
- Bachelor's degree (at least a 2:1) in STEM, Economics or another highly analytical field
- Masters
- PhD
Salary/Compensations
- £50,000 base salary
- Incentive Awards tied to performance
Benefits
- Incentive award tied to your performance
- Flexible working hours
- Training courses on programming languages like SQL & Python
- Training on behavioural skills like effective communication and presenting data analysis
- £1,000 learning budget each year
- Top-spec Macbook and accessories
- Knowledge-sharing sessions
- Team and company wide socials / events
- Lunch on Monzo twice a week
About the Company
- We’re on a mission to make money work for everyone.
- We are waving goodbye to the complicated and confusing ways of traditional banking.
- Our product offering has grown a lot in the last 10 years in the UK, including personal and business bank accounts, joint accounts, accounts for 16-17 year olds, a free kids account, and credit cards.
- Our UK customers can also save, invest and combine their pensions with us.
- We have a long history of creating magical moments for our customers with hot coral cards, get-paid-early feature, financial education on social media and award winning customer service.
- We’re not about selling products - we want to solve problems and change lives through Monzo.
Equal Opportunity
- 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.
- We are committed to making our recruitment process accessible and inclusive.
- We foster an inclusive environment for all people to do the best work of their lives.