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For Companies At a Glance
- Tasks: Analyse debt trends and build predictive models to improve credit recovery strategies.
- Company: Leading data consultancy in the UK with a dynamic Credit Risk team.
- Benefits: Hybrid working, competitive salary up to £54,000, and additional benefits.
- Why this job: Make a real impact in credit risk analytics while enjoying flexible work options.
- Qualifications: Strong SQL and Python skills, plus experience in credit risk analytics.
- Other info: Join a vibrant team with opportunities for professional growth.
The predicted salary is between 32400 - 54000 £ per year.
A leading data consultancy in the United Kingdom is seeking a skilled Revenue & Debt Data Scientist to join their dynamic Credit Risk function. This role involves conducting root cause analysis of debt accumulation trends and building predictive models to enhance credit recovery strategies.
The ideal candidate will have a strong background in SQL and Python, along with experience in credit risk analytics.
The position offers hybrid working flexibility and a competitive salary of up to £54,000 per annum plus benefits.
Credit Risk Data Scientist: Revenue & Debt Analytics in Sharlston employer: Cactus Search
Contact Detail:
Cactus Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist: Revenue & Debt Analytics in Sharlston
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can sometimes lead to job opportunities that aren’t even advertised.
✨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 discussing your experience.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practising your problem-solving approach will help you shine during technical assessments.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes speed up the process. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Credit Risk Data Scientist: Revenue & Debt Analytics in Sharlston
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 projects. We want to see how your skills align with 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 credit risk and how your background makes you the perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Analytical Skills: In your application, give examples of how you've conducted root cause analysis or built predictive models in the past. We’re looking for candidates who can demonstrate their analytical prowess, so don’t hold back on the details!
Apply Through Our Website: We encourage you to apply directly 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. Plus, it’s super easy!
How to prepare for a job interview at Cactus Search
✨Know Your SQL and Python 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 languages, especially in relation to credit risk analytics. Practising coding challenges can also help you feel more confident.
✨Understand Debt Accumulation Trends
Familiarise yourself with common debt accumulation trends and the factors that influence them. Be ready to discuss how you've conducted root cause analysis in the past and how it can apply to the role. This shows your analytical thinking and relevance to the position.
✨Prepare for Predictive Modelling Questions
Since the role involves building predictive models, be prepared to explain your approach to model development. Think about the methodologies you've used and be ready to discuss how you validate your models. This will demonstrate your technical expertise and problem-solving skills.
✨Show Enthusiasm for Hybrid Working
With hybrid working flexibility being a part of the job, express your enthusiasm for this arrangement. Share examples of how you've successfully worked in a hybrid environment before, highlighting your ability to stay productive and engaged, whether at home or in the office.
