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- Tasks: Transform data into actionable insights and lead predictive modelling for credit risk.
- Company: Join a dynamic team at the forefront of credit risk analytics.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for impactful projects.
- Why this job: Make a real difference in financial resilience and customer outcomes.
- Qualifications: Proficient in SQL and Python, with experience in credit risk analytics.
- Other info: Collaborative environment with strong career growth potential.
The predicted salary is between 43200 - 75600 £ per year.
Are you ready to turn data into action and make a tangible impact? We’re looking for a skilled and driven Revenue & Debt Data Scientist to join a dynamic Credit Risk function. This is a unique opportunity to work at the forefront of credit risk analytics, helping shape smarter collections strategies, reduce bad debt, and improve outcomes for customers.
In this pivotal role, you’ll lead deep-dive analysis into customer portfolio trends, build predictive models, and support the transition to an enterprise data lake. Your insights will directly influence operational improvements, strategic decisions, and long-term financial resilience.
What you’ll do:
- Conduct root cause analysis of debt accumulation trends.
- Build and refine predictive models for credit risk and debt recovery.
- Develop and maintain SQL-based reporting solutions to drive actionable insights.
- Collaborate across teams to align data governance, infrastructure, and reporting needs.
- Embed analytics into strategic decision-making and champion data-driven thinking.
What we’re looking for:
- Proficient in SQL for querying, joining, and transforming large datasets.
- Experienced in data cleansing, validation, and predictive modelling.
- Strong in Python for statistical analysis and able to communicate insights to non-technical stakeholders.
- Proven experience in credit risk analytics, debt management, or financial modelling.
- Comfortable working cross-functionally and translating data into actionable strategy.
- Familiarity with cloud platforms such as Azure, AWS, or Google Cloud.
- Degree (or equivalent) in Data Science, Mathematics, Statistics, or a related field.
- Experience migrating from traditional databases to data lake architectures.
- Background in Financial Services or other regulated industries.
- Exposure to SAP/DM9 environments.
- Knowledge of machine learning techniques relevant to credit risk.
What we offer:
- Hybrid working flexibility (South West).
- Competitive salary of up to £54,000 per annum + benefits.
- Opportunities to work on high-impact projects that shape strategy and operations.
If you’re passionate about using data to drive decisions and make a difference, we’d love to hear from you.
Revenue & Debt Data Scientist in Gloucester employer: Cactus Search
Contact Detail:
Cactus Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Revenue & Debt Data Scientist in Gloucester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions related to data science and credit risk. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your thoughts.
✨Tip Number 3
Showcase your skills through projects! Create a portfolio of your predictive models or SQL reporting solutions. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and making an impact.
We think you need these skills to ace Revenue & Debt Data Scientist in Gloucester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Revenue & Debt Data Scientist. Highlight your experience with SQL, predictive modelling, and any relevant projects that showcase your skills in credit risk analytics.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about data and how you can make a tangible impact at StudySmarter. Share specific examples of how you've turned data into actionable insights in previous roles.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and any experience with cloud platforms like Azure or AWS. We want to see how you’ve used these tools to drive results in your past work.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Cactus Search
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving SQL and predictive modelling. Be ready to discuss specific examples of how you've used data to drive decisions, especially in credit risk analytics. This will show your expertise and passion for the role.
✨Brush Up on Technical Skills
Make sure you're comfortable with SQL queries and Python for statistical analysis. Practise explaining complex concepts in simple terms, as you'll need to communicate insights to non-technical stakeholders. Consider doing a mock interview with a friend to refine your explanations.
✨Understand the Company’s Needs
Research the company’s current strategies in credit risk and debt management. Think about how your skills can help them improve their collections strategies and reduce bad debt. Tailor your answers to demonstrate how you can make a tangible impact in their operations.
✨Prepare Questions to Ask
Have a few thoughtful questions ready about the team dynamics, the transition to an enterprise data lake, or their approach to data governance. This shows your interest in the role and helps you assess if the company is the right fit for you.
