At a Glance
- Tasks: Analyse data to forecast financial health and inform risk management strategies.
- Company: Join an award-winning workplace recognised for its inclusive culture and employee support.
- Benefits: Enjoy competitive salary, 26 days annual leave, flexible benefits, and excellent parental leave.
- Why this job: Make a real impact in credit risk analysis while growing your career in a supportive environment.
- Qualifications: Proven experience in data analytics, strong coding skills in SQL and Python, and a quantitative degree.
- Other info: Flexible working options and opportunities for professional development await you.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a Senior Data Analyst to join our Credit Risk Portfolio Management team - a key function responsible for understanding and forecasting the financial health of the customer base. The role requires the use of advanced analytics to provide deep insights into credit risk and performance to inform our risk management strategy. This role is ideal for a proven senior analyst with strong technical and mathematical skills combined with the commercial acumen needed to translate insights into action.
Here’s a taste of what you’ll be doing:
- Partnering with Finance to develop and maintain debt forecasts to track performance vs. plan, forecast risk and deep dive into the drivers of variations to plan
- Developing scenario models to enable data-based decisioning within operational and strategic planning cycles
- Staying up to date with emerging analytical techniques and technologies, partnering with Data Science to deliver advanced segmentation and behavioural analysis
- Delivering and consulting on the advanced analytics required to support project delivery across the wider Credit Management function e.g. simulation models, data pipeline mock ups, statistically robust testing
- Translating analytical outputs into clear recommendations for business stakeholders, influencing decisions across debt prevention and collections strategy
- Liaising with Data Engineers to drive enhancements to data quality, availability and usability
Proven experience in a data analytics or credit risk role, ideally within utilities, financial services or other regulated industry:
- Strong coding skills in SQL, Python and PySpark for data extraction, transformation, modeling and forecasting
- Solid understanding of forecasting techniques, scenario modelling, and regression-based analytics
- Strong commercial acumen, with the ability to translate complex analytical findings into clear narratives with direct links to business value
- Excellent stakeholder engagement and communication skills, with confidence working across operational, strategic and technical teams
- A degree (or equivalent experience) in a quantitative discipline such as statistics, mathematics, economics or data science
It would be great if you had:
- Experience working with Databricks
- Understanding of macroeconomic and market drivers affecting customer affordability and credit risk
- Prior experience working across both residential and commercial consumer bases
- Experience working with credit bureau data
- A general understanding of accounting principles
Here’s what else you need to know:
- Role may close earlier due to high applications
- Competitive salary
- Location – Nottingham E.ON Next office, Trinity House, 2 Burton St, Nottingham NG1 4BX - with travel to our other sites when required
- Excellent parental leave allowance
- Award-Winning Workplace - We’re proud to be named a Sunday Times Best Place to Work 2025 and the Best Place to Work for 16–34-year-olds
- Outstanding Benefits - Enjoy 26 days of annual leave plus bank holidays, a generous pension, life cover, bonus opportunities and access to 20 flexible benefits with tax/NI savings
- Flexible & Family-Friendly - Our industry-leading hybrid and family-friendly policies earned us double recognition at the Personnel Today Awards 2024. We’re open to discussing how flexibility can work for you
- Inclusive & Diverse - We’re the only energy company in the Inclusive Top 50 UK Employers. We’re also proud winners of Best Employer for Women and Human Company of the Year—recognising our inclusive, people-first culture
- Support at Every Stage of Life - We’re Fertility Friendly and Menopause Friendly accredited, with inclusive support for everyone
- Accessible & Supportive - and will make any adjustments needed during the process
- Invested in Your Growth - From inclusive talent networks to top-tier development programmes, we’ll support your growth every step of the way
For all successful candidates. Due to the nature of this role your employment will be subject to a basic DBS (Disclosure Barring Service) check being carried out by ourselves via a 3rd party service provider.
Senior Data Analyst in Nottingham employer: E.ON Next Energy Limited
Contact Detail:
E.ON Next Energy Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst in Nottingham
✨Tip Number 1
Network like a pro! Reach out to current employees at E.ON Next on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your application noticed.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL, Python, and PySpark skills. Be ready to showcase how you've used these tools in past roles to drive insights and influence decisions.
✨Tip Number 3
Don’t just talk numbers; tell a story! When discussing your analytical findings, focus on how they’ve impacted business outcomes. This will show your commercial acumen and ability to translate data into action.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at E.ON Next.
We think you need these skills to ace Senior Data Analyst in Nottingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Analyst role. Highlight your experience in data analytics, credit risk, and any relevant technical skills like SQL and Python. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your skills can contribute to our Credit Risk Portfolio Management team. Keep it concise but impactful – we love a good story!
Showcase Your Analytical Skills: In your application, don’t forget to showcase your analytical skills and experience with forecasting techniques. We’re keen on seeing how you’ve used advanced analytics to drive decisions in previous roles. Be specific and give examples!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at E.ON Next Energy Limited
✨Know Your Numbers
As a Senior Data Analyst, you'll need to showcase your technical skills. Brush up on your SQL, Python, and PySpark coding abilities. Be ready to discuss specific projects where you've used these tools to extract and analyse data, and how your insights influenced business decisions.
✨Understand the Business Context
Make sure you understand the credit risk landscape and how it impacts financial health. Familiarise yourself with macroeconomic factors that affect customer affordability. This will help you translate complex analytical findings into actionable recommendations during the interview.
✨Prepare for Scenario Modelling Questions
Expect questions about scenario modelling and forecasting techniques. Prepare examples of how you've developed models in the past and the outcomes they produced. Being able to explain your thought process clearly will demonstrate your analytical prowess.
✨Engage with Stakeholders
Strong communication skills are key for this role. Think of examples where you've successfully engaged with stakeholders to influence decisions. Be ready to discuss how you can bridge the gap between technical analysis and business strategy, making your insights accessible to non-technical audiences.