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- Tasks: Transform data into actionable insights and shape smarter collections strategies.
- Company: Dynamic Credit Risk function at the forefront of analytics.
- Benefits: Hybrid working, competitive salary up to £54,000, and high-impact project opportunities.
- Why this job: Make a tangible impact on credit risk and improve customer outcomes.
- Qualifications: Proficient in SQL, Python, and experienced in credit risk analytics.
- Other info: Join a collaborative team with opportunities for professional growth.
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.
Desirable:
- 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.
Data Scientist employer: Cactus Search
Contact Detail:
Cactus Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and SQL reporting solutions. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your past projects. Practice explaining complex concepts in simple terms, as you'll need to communicate insights to non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience in SQL, Python, and credit risk analytics. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and how you can make a tangible impact at StudySmarter. Let us know why you’re the perfect fit for our team.
Showcase Relevant Projects: If you've worked on projects related to predictive modelling or debt management, don’t hold back! Include these in your application to demonstrate your hands-on experience and problem-solving skills.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
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 data analysis and predictive modelling. Be ready to discuss specific examples where your insights led to tangible outcomes, especially in credit risk or debt management.
✨Brush Up on SQL and Python
Make sure you’re comfortable with SQL queries and Python for statistical analysis. Practise explaining complex technical concepts in simple terms, as you’ll need to communicate your findings to non-technical stakeholders.
✨Showcase Your Collaborative Spirit
Prepare to discuss how you've worked cross-functionally in previous roles. Highlight instances where you aligned data governance or reporting needs with other teams, as collaboration is key in this role.
✨Stay Current with Cloud Technologies
Familiarise yourself with cloud platforms like Azure, AWS, or Google Cloud. Be ready to talk about any experience you have with migrating databases to data lakes, as this knowledge will set you apart from other candidates.
