This is a generalist role rather than one focused on a particular model type. You’ll work across models used for impairment, capital, stress testing, forecasting and credit decisioning, including IFRS 9 PD, LGD, EAD and economic response models; decision science scorecards and origination PD models; and Net Present Value (NPV) / unit economics models.
Strong data and analytical skills are a must, as is broad expertise in credit risk modelling and model risk management. You’ll have hands-on experience in model validation and/or development within financial services, and be comfortable getting into the data and code to form an independent view across different model types.
Your day-to-day
Leading hands-on independent validation across Monzo’s credit model portfolio – covering models used for IFRS 9 impairment, capital and stress testing, forecasting, credit decisioning and unit economics – and making sure they are fit for purpose, appropriately governed and performing as expected
Reviewing and challenging key model-led credit risk assessments, including impairment adequacy, ICAAP and stress testing, using independent analysis to assess assumptions, limitations and impacts
Developing a deep understanding of Monzo’s credit models and how they are used, and using this to provide impactful input and challenge to model developers and users
Contributing to making model validation more consistent, scalable and technology-enabled – building reusable analytical tools and tests, experimenting with AI-assisted approaches and helping the team embed them safely
Reviewing ongoing model performance monitoring to ensure our lending models perform within our risk thresholds, and providing support to our first line of defence teams when action is required
Performing statistical analyses, model replication and challenger work where appropriate to test assumptions, assess performance and strengthen validation conclusions
Improving and helping to embed our Model Risk Framework, including our policies, standards, model inventory, governance and validation approach. This means making sure we follow up-to-date regulatory expectations and that our processes remain proportionate and relevant as modelling techniques evolve
Writing clear and impactful model validation reports, and presenting the findings and actions in relevant committees
Partnering with colleagues in first line of defence credit strategy, modelling and finance teams – and with wider risk teams across Monzo – to support effective model governance and consistent validation standards across the organisation
You should apply if you
Have a strong background and practical experience in credit model development and/or validation across a range of model types. You’ll have meaningful experience with IFRS 9 impairment, Internal Ratings Based (IRB) or other capital models, alongside broader exposure to several areas such as stress testing, economic response, forecasting, decision science scorecards or NPV / unit economics modelling
Understand model risk management in practice, including independent validation, model governance, ongoing monitoring, model change and issue management, and how regulatory expectations apply across the model lifecycle
Are impact-driven and want to improve how validation is done, not only complete individual reviews. You can turn repeatable work into practical methods, tools or guidance that improve quality and consistency across the team.
Are curious about AI and automation, and can assess where they add value, the risks they introduce, and the controls and human oversight needed. Experience with AI-assisted analytical or coding tools is useful, but not essential
Are data driven, with strong analytical skills and deep knowledge of statistical techniques for credit and model risk. Strong SQL and Python skills are essential. You can produce clear, reusable and tested code, using collaborative practices such as version control, peer review and documentation. Experience with Tableau, Looker or similar is a plus.
Can assess models in the context of how they are used – including accounting, capital, credit strategy, risk appetite and customer outcomes – and can distinguish technical model performance from the wider risks of relying on the model
Have strong written and verbal communication skills, and are able to articulate problems and solutions using clear and simple language. This is particularly important for breaking down complex issues and priorities to non-experts
Have a track record of building and maintaining trusting relationships with stakeholders at all levels, and can provide effective and respectful challenge
Our technology stack
We rely heavily on the following tools and technologies (note we do not expect applicants to have prior experience of all them):
Google Cloud Platform for all of our analytics infrastructure
dbt and BigQuery SQL for our data modelling and warehousing
Python for data science and machine learning
Go to write our application code
AWS for most of our backend infrastructure
The interview process
Our interview process usually involves up to four main stages via Google Meet:
An initial call with our recruiter
A call with our Senior Model Validation Manager, the hiring manager for the role
A role-specific call with colleagues from our credit modelling and model risk teams. We’ll share a short case study in advance, but you won’t need to submit a written response; we’ll use it to guide the discussion during the interview.
A behavioural interview
🙌 What’s in it for you
💰 £79,000 – £93,000 + Incentive Awards tied to your performance benefits.
📍 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, and at times that suit you and your team.
📚 £1,000 learning budget each year to use on books, training courses and conferences.
🏡 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.
➕ Plus lots more! Read our full list of benefits.
We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo. You can read them here.
- We’ll close this role once we have enough applications for the next stage, so please apply as soon as you can – we don’t want you to miss out!
- #LI-TK1
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. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report.
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.
If you have a preferred name, please use it to apply. We don’t need full or birth names at application stage 😊
