Graduate Residual Value Analyst

Let us tell you more about the opportunity

Are you curious about how data shapes real‑world decisions? Do you enjoy working with numbers, spotting patterns, and turning insight into action? If you’re looking for a graduate role where your analysis genuinely matters - this could be the perfect place to start.

This is a fantastic opportunity for a graduate to build a career at the intersection of data analytics, financial services, and the automotive market, with a clear pathway for progression as you grow. Residual value is the predicted future value of a vehicle - and it plays a crucial role in pricing, risk management, and portfolio performance. In this role, your work will help shape commercially sound decisions, protect the business from risk, and ensure our pricing remains competitive and data‑led.

Here at Aldermore, your growth matters. We'll champion your development through a structured and targeted programme. 

What will your day look like?

• Monitor and analyse vehicle residual value performance across different products and vehicle cohorts.
• Compare forecast versus actual vehicle sale values to identify trends, drivers of variance, and emerging risks.
• Produce regular reports and insights to support pricing, portfolio management, and decision‑making.
• Carry out ad hoc analysis to answer commercial and risk‑focused questions from stakeholders.
• Manage, maintain, and improve residual value datasets, assumptions, and tracking tools.
• Extract, manipulate, and analyse data using tools such as Excel and other analytical systems, ensuring accuracy and quality.
• Support dashboards and MI reporting, identifying opportunities to improve automation and efficiency.
• Track external automotive market trends and benchmark internal assumptions against market data.

This role is designed to grow with you, offering increasing responsibility as your skills develop.

What do we expect from you?

We’re looking for graduates who are curious, analytical, and excited about using data to solve problems. You’ll bring:

• A degree in a numerate subject such as Mathematics, Economics, Engineering, Finance, Statistics, or similar (graduated in 2024, 2025, or 2026)
• Strong numerical and analytical skills with great attention to detail
• Confidence working with structured datasets
• Advanced Excel skills (experience with SQL, SAS, Python or Power BI is a bonus, not a must)
• The ability to explain data and insights clearly
• A proactive mindset and enthusiasm for learning

Training and development will be provided, and no prior industry experience is required.

What can you expect from us?

• Hybrid working policy – 2 days onsite in our central Cardiff office, 3 days working from home
• Structured and targeted development programme to support your career
• A friendly and flexible culture, the same as how we work with our customers
• A growing organisation that means there’s lots of opportunities to progress
• A drive for continuous improvement, which you will be empowered to get behind from day one
• And of course, you will be rewarded competitively, with a great range of core benefits including; annual bonus, up to 10% employer contribution pension, private medical with BUPA and 38 days holiday (including bank holidays)

Recruitment process:

• Advert closing date – Friday 27th March
• Initial call with recruiter – 30 minutes
• SHL online assessment – 25 minutes
• In-person assessment – 08:45-13:00 on Friday 24th April *please only apply if able to attend this date
• Start date: September 2026

Still curious?

Join us and we’ll make the same promises to you as a colleague, as we do to each of our customers. We’re committed to building a working environment that values respect, diversity, and compassion. We welcome people regardless of age, disability, gender identity, marital status, race, faith or belief, sexual orientation, socioeconomic background, and whether you’re pregnant or on family leave. Please note: we have a thorough screening and referencing process, which includes criminal record checks