Risk/Forecasting Modeller

JR United Kingdom; Slough; On-site; GBP 65,000 - 85,000; Full time

Job summary

A leading UK automotive leasing organization is seeking an Asset Risk Senior Risk Modeller. This role involves managing model risk, delivering complex forecasts, and engaging collaboratively with stakeholders to ensure robust financial risk management. The successful candidate will have substantial experience in data analysis, model development, and the ability to communicate technical concepts to diverse audiences.

Qualifications

• Over 3 years of experience in forecasting, data analysis, or a related field.
• Experience managing complex projects and coaching analysts.
• Experience in the specific industry relevant to the forecasting role (e.g., finance, retail, manufacturing) is highly valuable.

Responsibilities

• Support the delivery of the Asset Risk strategy in alignment with business needs.
• Oversee operational delivery of the model risk management framework.
• Engage in critical thinking and activity for BAU model delivery.

Skills

Planning

Modelling

Accuracy & attention to detail

Problem solving skills

Communication skills

Commercial awareness

Education

Bachelor’s or Masters in Statistics, Mathematics, Economics, Data Science

Tools

R

Python

SAS

Job description

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Peaple Talent has partnered with a leading UK automotive leasing organisation who are currently looking at recruiting for Asset Risk Senior Risk Modeller. The role will sit in the Asset Risk Function, which has the responsibility for forecasting the operation’s key financial risks, including Residual Value and SMR, Insurance Lease Pricing, Economic Capital, as well as producing the customer pricing. The role sits within the Asset Risk Modelling Team, operating in a matrix way of working, responsible delivering a strong model risk management framework, and ensuring all forecast models are robustly implemented, operated, enhanced and developed in conjunction with joint ownership for the outcomes and outputs with business SME’s.

Key responsibilities

• You will proactively support and inform the delivery of the Asset Risk strategy in alignment with the needs of the wider business strategy
• You will work with the Modelling Manager to oversee the operational delivery of the model risk management framework in Asset Risk, ensuring model health, reporting, processing, auditing and reporting requirements are met and provide steer and challenge to ensure improvements are approved and delivered
• You will take the lead and proactively engage with the critical thinking and operational activity needed for the accurate and timely delivery of the critical BAU requirements for all key models associated with residual value forecasting, maintenance spend, insurance, customer pricing, and economic capital
• You will maintain a deep understanding of, and be responsible for the challenging of, the model components - design principles, use of data, assumptions, applied statistical and modelling techniques – for the BAU models, helping to create and deliver the effective communication required to bridge the gap between the models and Asset Risk deliverables
• You will take the lead and proactively engage with the critical thinking and activity required to deliver the strategic projects from the Modelling team, ensuring all deliverables and outcomes are jointly owned with business SME’s
• You will work with the Modelling Lead to ensure the Modelling Team are as engaged with explaining and owning the outputs and outcomes as they are with operating and developing our models, and with the equivalent engagement from non-modelling teams
• You will proactively challenge the way we work, and feed into the Asset Risk Strategy roadmap, and support in ad hoc queries where possible
• You will form collaborative relationships to ensure the Model Team deliverables (BAU and strategic projects) are effectively managed and delivered in line with a matrix way of working approach across the Asset Risk Operational Teams and fellow Asset Risk output owners
• You will play a pivotal role in ensuring the AR Operational Teams (Programme, Product, Modelling and Data) work closely with each other to support on cross over areas (e.g. tools) and reduce the opportunity for knowledge gaps
• You will be an effective coach and mentor for the wider Modelling Team, working with the Modelling Manager to ensure the team and individuals have the right skills and development paths to meet the needs of the business.
• You will be an advocate for Asset Risk, and work with colleagues around the business to promote best practices and skills & knowledge sharing.
• You will develop collaborative and enduring relationships with the Asset Risk and wider business leadership teams, relevant stakeholders, and be an advocate for Asset Risk and our ways of working
• You will proactively work with the Modelling Lead to engage with relevant 3rd parties (industry bodies, commentators and experts) to ensure Asset Risk activities are appropriately aligned with external best practice.

About you

• Planning: Ability to coordinate multiple stakeholders, colleagues and deadlines
• Modelling: Ability to understand, operate, and explain complex models
• Accuracy & attention to detail: Ensuring accuracy in models and forecasts.
• Problem solving skills: Ability to develop solutions for complex financial problems.
• Communication skills: Can explain technical concepts to non-technical stakeholders.
• Commercial awareness: Can understand the business environment, market trends, and the financial impact of decisions to align models with the organisation's strategic goals.
• A degree (Bachelor’s or Masters) in Statistics, Mathematics, Economics, Data Science, or a related field
• Over 3 years of experience in forecasting, data analysis, or a related field
• Over 3 years experience of delivering complex model updates (operational and development) with the effective communication of model outcomes
• Proven experience with statistical software (e.g., R, Python, SAS) and forecasting tools
• Experience managing complex projects and coaching analysts
• Experience in the specific industry relevant to the forecasting role (e.g., finance, retail, manufacturing) is highly valuable
• Experience with advanced analytical techniques, including machine learning and predictive modelling