Credit Model Validation Analyst

📍London | 💰 £70-90k + stock options + Benefits | Data

About us:

At Monzo we believe there’s a better way to do banking - we care deeply about our customers, are innovative and execute quickly.

We encourage an open, collaborative, inclusive working environment. We’re looking to revolutionise the way people manage their finances by putting them in control and promoting their financial wellbeing. Our Borrowing business is growing rapidly (both on our existing products, and with the planned launch of new products). We aim to create a genuine feel-good factor when it comes to personal credit, and are looking for driven, analytical and creative individuals to help us achieve this goal. 

We are scaling up our second line of defence Credit Risk team to support the rapid growth and evolution of our portfolio. This role is pivotal for the team as the successful candidate will help ensure the models we use are not only good for Monzo but what's best for our customers. The role will provide independent validation and oversight of models across critical business disciplines such as IFRS 9 (PD, LGD, EAD, macroeconomic models), ICAAP, Borrowing decisions and strategy. 

Strong data and analytical skills are a must, as is a deep expertise in credit risk modelling, and at least some of the following areas: scorecard modelling, IFRS9 provision methodology, Net Present Value modelling, capital modelling and stress testing.

Monzo’s Credit Risk (Risk and Compliance) and Data Team

Our mission in the Risk and Compliance is to To help Monzo grow safely

The second line of defence Model Oversight team (that’s us!) provides support to our colleagues in Borrowing, Fincrime & Fraud and Finance to help Monzo grow safely. 

Our Data team's mission is to Enable Monzo to Make Better Decisions, Faster

At the core of this mission sits our data platform. We're great believers in powerful, real-time analytics and empowerment of the wider business. Our engineers collect analytics events from their microservices, and upload these into our Data stack for analysis. We optimise for simplicity and re-usability – all our data lives in one place and is made available via our data warehouse in Google BigQuery.

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
• Go to write our application code
• AWS for most of our backend infrastructure

Your day-to-day responsibilities:   

• Perform independent model validation as part of our second line of defence Credit Risk teams and making sure the credit risk models are fit for purpose (including IFRS 9, NPV, Stress Testing, ICAAP, Decision Science scorecards, economic response models)
• Review ongoing model performance monitoring to ensure the Borrowing models are performing within risk thresholds and providing support to the  Borrowing model development team when further action is required
• Review and challenge our provisions and adequacy, including reviewing the 1st line of defence analysis; performing independent analysis and testing; actively contributing into discussions of emerging regulatory changes and best practices (SS1/23; ‘Dear CFO letter’); presenting materials to the monthly impairment council and building governance and controls around the framework
• Improve our Model Risk Framework including policies, standards and procedures helping to embed best practice in the business. Making sure it follows up-to date regulatory guidelines and it is relevant for modern modelling techniques
• Write clear and impactful model validation reports and present the findings in relevant committees
• Build relationships with first line of defence Borrowing credit strategy and modelling teams and wider risk teams to support the embedding of the model risk framework and an understanding of model validation practices to help Monzo grow safely.
• Support the effective operation of the Model Risk Oversight Committee as a regular attendee, contributing to the group discussion to improve model risk management.

You should apply if:

• You have a strong background and experience in credit models development and/or validation in some of the following areas: IFRS 9 (PD, EAD, LGD, economic response models), IRB, stress testing, decision science scorecards (including machine learning models), net present value, forecasting
• You have strong analytical skills and a track record of using these to deliver technical projects and in-depth knowledge of statistical techniques for management of credit and model risk
• You have a solid technical toolkit. SQL and either Python or R is a must-have, a data visualisation tool (such as Tableau, PowerBI, Looker) is a plus
• You can convey problems and solutions using clear and simple language, both written and verbal (see Monzo’s tone of voice guide). This is particularly important for communicating complex issues and priorities to non-experts
• You're impact driven and eager to have a real positive impact on the company, our products, our users and your team-mates
• You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• You're a team player whom your colleagues can rely on
• You can provide effective challenge whilst building strong, respectful relationships
• You are keen to grow your knowledge in both business and technology

The Interview Process:

Our interview process involves 4 main stages: 

1. Recruiter Call
2. Initial Call with the hiring manager
3. Take Home Task (preparation for the role specific interview)
4. Role specific
5. Values & collaboration

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 [email protected]

What’s in it for you:

💰 circa £70-90k base salary➕ plus stock options

📍 London (one to two days a week)

⏰ 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