Model Validation Senior Manager
Monzo Cardiff, London or Remote (UK)Est. Est. GBP 65,000–95,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Machine Learning
- Data Science
🚀 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 ❤️
📍London or Remote (UK) | 💰 £85,000 - £105,000 + Incentive Awards tied to your performance + Benefits
⭐Our Model Oversight team
The second line of defence Model Oversight team (that’s us!) provides support to our colleagues in Borrowing, Fincrime & Fraud, Finance and Operations to help Monzo grow safely. We’re looking for a Model Validation Senior Manager - Gen AI to lead the teams’ oversight of Generative AI models/use cases (primarily built across Monzo’s Operations squads) to provide assurance that the models/use cases we use are not only good for Monzo but what's best for our customers.
🔑You’ll play a key role by...
Driving the embedding of the Model Risk Framework for Generative AI use cases across Monzo
Lead the collaboration with the first line of defence teams to strengthen policies, standards and procedures for Generative AI model, use case, system design and build, implementation, governance, monitoring and use. Helping to embed best practice of Generative AI across the business.
Own the setting and maintenance of Generative AI validation methods, evidence expectations and reusable technical assets with relevant 1LoD modelling teams, applicable across all model risk areas.
Convert modelling/validation experience into controlled playbooks, tests and working examples that can be applied to 2LoD Validation standards and processes for all Generative AI models, use cases, systems overseen by the 2LoD Model Oversight team.
Coach Generative AI validation methodologies, to 2LoD Model Oversight colleagues, whom already have transferable Machine Learning skills, to reduce reliance on any single specialist for the validation of Generative AI models, use cases, systems so it can be consistently applied across Financial, Credit and Fincrime/Fraud models.
Leading the 2LoD Oversight of Operational Model Risk
Perform, and oversee, independent model validations of new Operational models (primarily Generative AI models, use cases, systems), and changes to existing, using proportionate modelling techniques depending on the level of complexity applied. This includes writing clear and impactful model validation reports and presenting the findings in relevant committees.
Build relationships with first line of defence modelling teams that develop Operational Models, and wider risk teams, to support the embedding of the model risk framework to help Monzo grow safely.
Review ongoing model performance monitoring to ensure Operational models are performing within risk thresholds and providing support to the relevant model development team when further action is required
Monitoring and measuring the overall level of Operational model risk that Monzo operates, and driving action plans with first line teams and appropriate governance forums to mitigate residual model risk within desired risk appetite.
Being a senior advocate of Model Risk Management best practices
Support the effective operation of the Model Risk Oversight Committee as a regular attendee, contributing to the group discussion to improve model risk management.
Promote and help embed a strong risk culture,
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