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- Tasks: Conduct data analysis and build predictive models in credit risk.
- Company: Leading recruitment firm with a dynamic Credit Risk function.
- Benefits: Competitive salary up to £54,000 and hybrid working options.
- Why this job: Join a team making impactful data-driven decisions in a growing field.
- Qualifications: Strong SQL and Python skills with credit risk analytics experience.
- Other info: Exciting opportunity for career growth in a collaborative environment.
The predicted salary is between 43200 - 57600 £ per year.
A leading recruitment firm is looking for a skilled Revenue & Debt Data Scientist to join their dynamic Credit Risk function in Gloucester. This role involves conducting data analysis, building predictive models, and supporting the migration to an enterprise data lake.
The ideal candidate will have a strong background in SQL and Python, with experience in credit risk analytics and data-driven decision-making.
A competitive salary of up to £54,000 per annum and hybrid working options are offered.
Credit Risk Data Scientist — Hybrid (South West) in Gloucester employer: Cactus Search
Contact Detail:
Cactus Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist — Hybrid (South West) in Gloucester
✨Tip Number 1
Network like a pro! Reach out to folks in the credit risk and data science fields on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL and Python projects, especially those related to credit risk analytics. This will give you an edge when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. We recommend practising with friends or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Credit Risk Data Scientist — Hybrid (South West) in Gloucester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in SQL and Python, as well as any relevant credit risk analytics. We want to see how your skills match the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how you can contribute to our Credit Risk function. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any projects related to predictive modelling or data analysis, make sure to mention them. We’re interested in seeing how you’ve applied your skills in real-world scenarios, so include any relevant examples!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications 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
Make sure you brush up on your SQL and Python skills before the interview. Be prepared to discuss specific projects where you've used these tools, especially in credit risk analytics. This will show that you not only understand the theory but can also apply it practically.
✨Predictive Modelling Examples
Have a couple of examples ready where you've built predictive models. Talk about the methodologies you used, the challenges you faced, and how your models impacted decision-making. This will demonstrate your hands-on experience and analytical thinking.
✨Understand the Migration Process
Since this role involves supporting the migration to an enterprise data lake, do some research on what that entails. Be ready to discuss how you would approach this task and any relevant experiences you have had with data migration or integration.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's credit risk function and their data strategy. This shows your genuine interest in the role and helps you assess if the company is the right fit for you. Plus, it gives you a chance to engage with the interviewers on a deeper level.
