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- Tasks: Analyse data to support customers with payment challenges and enhance credit risk insights.
- Company: Leading renewable energy firm in Greater London with a focus on inclusivity.
- Benefits: Flexible salary, inclusive work culture, and opportunities for professional growth.
- Why this job: Make a difference in the renewable energy sector while honing your data skills.
- Qualifications: Strong SQL and Python skills, plus a basic understanding of machine learning.
The predicted salary is between 28800 - 43200 £ per year.
A leading renewable energy firm in Greater London is seeking a skilled individual to join their credit risk team. The role emphasizes strong data analytics and communication skills to support customers facing payment struggles.
Candidates should have excellent SQL and Python skills, alongside a basic understanding of machine learning.
A flexible approach to salary and a commitment to an inclusive work environment are core to this company culture.
Data Analyst - Python/ML for Credit Risk & Insights employer: Octopus Energy Group
Contact Detail:
Octopus Energy Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Python/ML for Credit Risk & Insights
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy sector, especially those working in credit risk. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects using Python or SQL, make sure to highlight them during interviews. Real-world examples can really set you apart from the competition.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your machine learning basics and be ready to discuss how you’d apply them in a credit risk context. Confidence in your knowledge can make a huge difference.
✨Tip Number 4
Don’t forget to apply through our website! We’re all about making connections and finding the right fit, so get your application in and let’s see if we can help you land that dream job!
We think you need these skills to ace Data Analyst - Python/ML for Credit Risk & Insights
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your SQL and Python skills, as well as any experience with machine learning. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data analytics and how you can contribute to our credit risk team. Keep it concise but engaging – we love a good story!
Showcase Your Communication Skills: Since this role involves supporting customers facing payment struggles, it’s crucial to demonstrate your communication skills. Include examples of how you've effectively communicated complex data insights in the past.
Apply Through Our Website: We encourage you to apply directly 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 from us!
How to prepare for a job interview at Octopus Energy Group
✨Know Your Data Tools
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've used these tools, especially in relation to data analysis and credit risk. This will show that you not only understand the technical side but can also apply it practically.
✨Showcase Your Communication Skills
Since the role involves supporting customers facing payment struggles, practice explaining complex data insights in simple terms. Think of examples where you've had to communicate difficult information effectively. This will demonstrate your ability to bridge the gap between data and customer understanding.
✨Understand Machine Learning Basics
Even if you're not a machine learning expert, having a basic understanding is crucial. Familiarise yourself with common algorithms and their applications in credit risk. Be prepared to discuss how machine learning can enhance data analysis and decision-making in this context.
✨Embrace Inclusivity
Research the company's commitment to an inclusive work environment. Be ready to share your thoughts on diversity and inclusion in the workplace. This shows that you align with their values and are keen to contribute positively to their culture.
