Risk/Forecasting Modeller

JR United Kingdom; London; On-site; GBP 50,000 - 90,000; Full time

Job summary

Join a leading UK automotive leasing organization as an Asset Risk Senior Risk Modeller. This exciting role involves overseeing model risk management, delivering strategic projects, and collaborating with cross-functional teams. You will leverage your expertise in forecasting and data analysis to drive key financial insights and ensure model accuracy. With a strong focus on communication and problem-solving, you'll mentor and coach the Modelling Team while advocating for best practices in Asset Risk. This is an exceptional opportunity to make a significant impact in a dynamic and innovative environment.

Qualifications

• 3+ years in forecasting and data analysis with strong attention to detail.
• Experience in managing projects and delivering complex model updates.

Responsibilities

• Support the delivery of the Asset Risk strategy aligned with business goals.
• Lead and engage in activities for timely delivery of BAU requirements.

Skills

Forecasting

Data Analysis

Model Risk Management

Communication

Problem Solving

Commercial Awareness

Education

Degree in Statistics

Degree in Mathematics

Degree in Economics

Degree in Data Science

Tools

R

Python

SAS

Job description

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, and Economic Capital, as well as customer pricing. The role is part of the Asset Risk Modelling Team, which operates in a matrix structure to ensure robust model risk management, implementation, operation, and development, with shared ownership of outcomes with business SMEs.

Key responsibilities

• Support and inform the delivery of the Asset Risk strategy aligned with the broader business goals.
• Oversee the operational delivery of the model risk management framework, ensuring model health, reporting, processing, and auditing are maintained, and propose improvements.
• Lead and engage in activities for the accurate and timely delivery of BAU requirements 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 communication between the models and Asset Risk deliverables.
• Lead strategic projects within the Modelling team, ensuring joint ownership with business SMEs.
• Collaborate with the Modelling Lead to ensure team engagement with model outputs and development, fostering cross-team understanding and ownership.
• Challenge existing processes, contribute to the Asset Risk Strategy roadmap, and support ad hoc queries.
• Build collaborative relationships to ensure effective management and delivery of BAU and strategic projects across teams.
• Facilitate close cooperation among Asset Risk Operational Teams to support cross-over areas and minimize knowledge gaps.
• Mentor and coach the wider Modelling Team, working with the Modelling Manager to develop skills and career paths.
• Promote Asset Risk best practices, skills sharing, and external engagement with industry bodies and experts.
• Develop and maintain relationships with Asset Risk and broader business leadership, advocating for Asset Risk initiatives and practices.

About you

• Planning: Skilled in coordinating multiple stakeholders, deadlines, and priorities.
• Modelling: Proficient in understanding, operating, and explaining complex models.
• Accuracy & attention to detail: Committed to precision in models and forecasts.
• Problem solving: Capable of developing solutions for complex financial challenges.
• Communication: Able to convey technical concepts to non-technical audiences.
• Commercial awareness: Understanding of business environment, market trends, and strategic financial impacts.
• A degree in Statistics, Mathematics, Economics, Data Science, or a related field.
• Over 3 years of experience in forecasting, data analysis, or related areas.
• Experience in delivering complex model updates and communicating outcomes effectively.
• Proficiency with statistical software (R, Python, SAS) and forecasting tools.
• Experience managing projects and coaching analysts.
• Relevant industry experience (finance, retail, manufacturing) is highly valuable.
• Experience with advanced analytical techniques, including machine learning and predictive modelling.