Peaple Talent has partnered with a leading UK automotive leasing organisation to recruit for the role of Asset Risk Senior Risk Modeller. This position is within the Asset Risk Function, responsible for forecasting key financial risks such as Residual Value, SMR, Insurance Lease Pricing, Economic Capital, and customer pricing. The role is part of the Asset Risk Modelling Team, which operates in a matrix structure to ensure robust model risk management, model development, and operational excellence.
Key responsibilities
- Support and contribute to the Asset Risk strategy aligned with overall business goals.
- Oversee operational delivery of the model risk management framework, ensuring model health, reporting, auditing, and continuous improvement.
- Lead and manage critical BAU model activities related to residual value, maintenance, insurance, customer pricing, and economic capital forecasts.
- Maintain a deep understanding of model components, challenge assumptions, and communicate effectively with stakeholders.
- Drive strategic projects, ensuring joint ownership and successful delivery with business SMEs.
- Engage with non-modelling teams to ensure model outputs are well explained and owned.
- Challenge current processes, contribute to the Asset Risk Strategy roadmap, and handle ad hoc queries.
- Build collaborative relationships within Asset Risk teams and promote best practices and knowledge sharing.
- Work with external industry bodies and experts to align with external best practices.
About you
- Strong planning skills to coordinate multiple stakeholders and deadlines.
- Ability to understand, operate, and explain complex models.
- High attention to detail and accuracy in models and forecasts.
- Problem-solving skills for complex financial issues.
- Excellent communication skills to explain technical concepts to non-technical audiences.
- Commercial awareness of the business environment and market trends.
- Degree in Statistics, Mathematics, Economics, Data Science, or related field.
- Over 3 years of experience in forecasting, data analysis, or related areas.
- Proven experience in delivering complex model updates and communicating outcomes.
- Experience with statistical software such as R, Python, SAS, and forecasting tools.
- Experience managing projects and coaching analysts.
- Industry experience relevant to forecasting (e.g., finance, retail, manufacturing) is highly valued.
- Knowledge of advanced analytical techniques, including machine learning and predictive modeling.