Risk/Forecasting Modeller

JR United Kingdom; City Of London; On-site; GBP 50,000 - 80,000; Full time

Job summary

A leading UK automotive leasing organization is seeking a Risk/Forecasting Modeller in London. This role involves forecasting financial risks and managing model operations within the Asset Risk Function. Ideal candidates will possess a strong educational background, over three years of relevant experience, and advanced modelling skills. Applicants are expected to drive strategic initiatives while collaborating closely with stakeholders to ensure model accuracy and best practices.

Qualifications

• Over 3 years in forecasting or data analysis.
• Experience delivering complex model updates.
• Knowledge of machine learning and predictive modeling.

Responsibilities

• Support delivery of Asset Risk strategy and model management.
• Lead operational activities on residual value forecasting.
• Drive strategic projects ensuring timely delivery.

Skills

Planning

Modelling

Attention to Detail

Problem-solving

Communication

Commercial Awareness

Education

Degree in Statistics

Degree in Mathematics

Degree in Economics

Degree in Data Science

Tools

R

Python

SAS

Job description

Social network you want to login/join with:

Risk/Forecasting Modeller, London (City of London)

Client: Peaple Talent

Location: London (City of London), United Kingdom

Job Category: Other

EU work permit required: Yes

Job Views:

3

Posted:

16.06.2025

Expiry Date:

31.07.2025

Job Description:

Peaple Talent has partnered with a leading UK automotive leasing organisation which is currently recruiting for an Asset Risk Senior Risk Modeller. The role is part of the Asset Risk Function, responsible for forecasting key financial risks such as Residual Value, SMR, Insurance Lease Pricing, Economic Capital, and customer pricing. The Asset Risk Modelling Team operates within a matrix structure, ensuring robust model risk management, and delivering accurate, reliable forecast models in collaboration with business SME’s.

Key responsibilities:

• Support and inform the delivery of the Asset Risk strategy aligned with the wider business goals.
• Oversee the operational delivery of the model risk management framework, ensuring model health, reporting, auditing, and processing requirements are met, and provide guidance for improvements.
• Lead the critical operational activities for models related to residual value forecasting, maintenance spend, insurance, customer pricing, and economic capital.
• Maintain a deep understanding of model components, challenge assumptions, and facilitate effective communication between models and Asset Risk deliverables.
• Drive strategic projects, ensuring joint ownership with business SME’s and timely delivery.
• Ensure engagement and ownership of model outputs within the modelling team and with non-modelling teams.
• Challenge current practices, contribute to the Asset Risk Strategy roadmap, and support ad hoc queries.
• Build collaborative relationships to manage and deliver team outputs effectively within a matrix working environment.
• Foster close cooperation among Asset Risk operational teams to support cross-functional areas and reduce knowledge gaps.
• Mentor and coach the modelling team, ensuring skill development and career progression.
• Promote best practices and knowledge sharing across Asset Risk and the wider organization.
• Develop relationships with external industry bodies and experts to align with best practices.

About you:

• Strong planning skills: ability to coordinate multiple stakeholders and deadlines.
• Advanced modelling skills: ability to understand, operate, and explain complex models.
• Attention to detail: ensuring accuracy in models and forecasts.
• Problem-solving skills: developing solutions for complex financial issues.
• Excellent communication skills: explaining technical concepts to non-technical stakeholders.
• Commercial awareness: understanding market trends and aligning models with strategic goals.
• Educational background: Degree in Statistics, Mathematics, Economics, Data Science, or related field.
• Experience: Over 3 years in forecasting, data analysis, or related fields, with proven experience in delivering complex model updates and using statistical software (e.g., R, Python, SAS).
• Project management and coaching experience, preferably within relevant industries such as finance, retail, or manufacturing.
• Knowledge of advanced analytical techniques, including machine learning and predictive modeling.