Remote opportunity at
MonzoSenior Machine Learning Manager, Borrowing
Monzo is recruiting a Senior Machine Learning Manager to lead an ML scientist team within its Borrowing area. The posting describes Borrowing as one of the…
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About This Role
Monzo is recruiting a Senior Machine Learning Manager to lead an ML scientist team within its Borrowing area. The posting describes Borrowing as one of the company's main growth engines, now moving into new customer segments and building the underwriting capability needed for Europe. The role can be based in London on a hybrid pattern, or carried out entirely remotely across the UK with occasional trips to London. Pay ranges…
Job Description
Monzo is recruiting a Senior Machine Learning Manager to lead an ML scientist team within its Borrowing area. The posting describes Borrowing as one of the company's main growth engines, now moving into new customer segments and building the underwriting capability needed for Europe. The role can be based in London on a hybrid pattern, or carried out entirely remotely across the UK with occasional trips to London. Pay ranges from £138,000 to £176,000, and comes with stock options, incentive awards and benefits.
The manager would define the Borrowing machine learning roadmap covering UK expansion, new customer groups and entry into the EU. Work covers underwriting, pricing, credit limits and lifecycle decisions, with the aim of improving current models while building capability that scales into new markets. Focus areas include bringing in new data sources and speeding up feature engineering, drawing on Open Banking feeds, transaction analytics and outside data for credit decisions, and raising standards for model quality, governance, tooling and iteration speed. The role also involves hiring and developing the ML team and collaborating with credit strategy, product, platform, validation, data and engineering colleagues.
Required experience includes a strong command of ML, statistics and decisioning systems, and deep background in credit risk and lending. Applicants should have built, deployed and iterated credit models in production, and have led senior ML scientists. Cross-functional leadership and experience turning strategy into delivery in a regulated environment are also needed. Work across more than one market and experience with advanced ML or AI on structured financial data would be a clear advantage.
The stack includes Google Cloud Platform, BigQuery, SQL, dbt, Python and the PyData libraries, Google AI Platform, AWS, and Go for backend services. Applicants do not need prior experience with all of these tools. The interview process comprises a 30-minute recruiter call, a 45-minute initial call, a 60-minute ML technical interview, a 60-minute people leadership interview and a 60-minute product and credit ML interview, all held on Google Meet.
Responsibilities
- Lead an ML scientist team and set the Borrowing roadmap for UK growth, new segments and EU expansion
- Improve models for underwriting, pricing, credit limits and lifecycle decisions for current products
- Widen the data used in models and shorten the time needed for feature engineering and model delivery
- Develop transaction intelligence and the use of Open Banking and external data in credit decisions
- Build underwriting capability that can be reused across products, segments and markets
- Hire, lead and develop a high-performing ML team
- Raise standards for model quality, governance, tooling and iteration speed
Requirements
- Strong command of ML, statistics and decisioning systems
- Extensive background in credit risk and lending
- Hands-on record of building, deploying and refining credit models in production
- Record of leading and growing senior ML scientists
- Ability to guide work across credit strategy, product, platform and model validation groups
- History of converting strategy into delivery in a regulated setting
Qualifications
- Work spanning several markets (a welcome addition)
- Familiarity with sophisticated ML techniques and AI applied to structured financial data (a welcome addition)
Core Skills
Benefits
- Stock options and incentive awards tied to performance
- Annual learning allowance of £1,000 for books, courses and conferences
- Help with relocation to the UK and visa sponsorship
- Flexible working hours and home-working setup support for remote staff
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the salary?
The posting gives a range of £138,000 to £176,000, with stock options, incentive awards and benefits.
Can the role be done remotely?
Yes, the posting says it can be carried out entirely remotely across the UK with occasional trips to London, or on a hybrid pattern based in London.
What are the key requirements?
Applicants need strong machine learning and credit risk experience, a record of deploying credit models in production, and experience leading senior ML scientists.
What does the interview process involve?
It has five stages covering a recruiter call, an initial call, an ML technical interview, a people leadership interview and a product and credit ML interview, all held on Google Meet.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.