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- Tasks: Design forecasting models for credit performance and collaborate with data scientists.
- Company: High-growth analytics firm with a focus on innovation.
- Benefits: Competitive compensation, robust benefits package, and equity participation.
- Why this job: Make a real impact in credit forecasting while working in a hybrid environment.
- Qualifications: Strong programming skills in Python and an MSc or PhD in a quantitative field.
- Other info: Exciting opportunity for career growth in a dynamic team.
The predicted salary is between 36000 - 60000 £ per year.
A high-growth analytics firm seeks a Data Specialist to design forecasting models for credit performance and collaborate with data scientists. The role involves developing correlation frameworks and simulation engines, requiring strong programming skills in Python and an MSc or PhD in a quantitative field.
This position offers competitive compensation, a robust benefits package, and meaningful equity participation, with hybrid work arrangements in London.
Research Data Scientist - Credit Forecasting (Hybrid, London) employer: Intellect Group
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Data Scientist - Credit Forecasting (Hybrid, London)
✨Tip Number 1
Network like a pro! Reach out to current or former employees in the analytics field, especially those who have worked on credit forecasting. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your programming projects in Python, especially any related to forecasting models or data analysis. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your coding skills and understanding correlation frameworks. We can even set up mock interviews with friends or use online platforms.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed there that you won’t find anywhere else.
We think you need these skills to ace Research Data Scientist - Credit Forecasting (Hybrid, London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your programming skills in Python and any relevant experience in developing forecasting models. We want to see how your background aligns with the role, so don’t be shy about showcasing your MSc or PhD in a quantitative field!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about credit forecasting and how your skills can contribute to our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects: If you've worked on any relevant projects, whether in academia or industry, make sure to mention them. We’re interested in your experience with correlation frameworks and simulation engines, so give us the details that demonstrate your expertise!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Intellect Group
✨Know Your Models
Make sure you’re well-versed in forecasting models and correlation frameworks. Brush up on your knowledge of credit performance metrics and be ready to discuss how you would approach designing these models.
✨Show Off Your Python Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to data analysis and model development.
✨Collaborative Mindset
This role involves working closely with other data scientists, so be prepared to discuss your experience in collaborative projects. Share examples of how you’ve successfully worked in teams to achieve common goals.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to credit forecasting and their data strategies. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
