At a Glance
- Tasks: Create impactful credit models and scorecards using advanced data science techniques.
- Company: Join a relaxed, innovative environment similar to Facebook or Google.
- Benefits: Enjoy competitive compensation and a vibrant work culture.
- Why this job: Make a real difference in the financial sector with your data skills.
- Qualifications: Experience in model creation, strong SQL, and proficiency in Python or R.
The predicted salary is between 50000 - 70000 € per year.
Location: London, United Kingdom
Posted about 1 year ago
Tech stack:
- Python
- R
- Artificial Intelligence
- SQL
Skills Required:
- Experience creating models/scorecards which are used in production
- Strong SQL
- Strong skills in Python or R
- Strong understanding of data warehousing
- AI Tooling
Work Environment:
The environment is that of Facebook or Google, relaxed and open.
Compensation: Competitive
Role type: Full time
Visa sponsorship: Not provided
Benefits & perks: —
Data Scientist - Credit/Scorecard modelling in London - Quant Capital employer: Quant Capital
At Quant Capital, we pride ourselves on fostering a dynamic and innovative work culture that mirrors the best of tech giants like Facebook and Google. Our London office offers competitive compensation, a relaxed environment, and ample opportunities for professional growth, making it an ideal place for Data Scientists looking to make a meaningful impact in credit and scorecard modelling.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Credit/Scorecard modelling in London - Quant Capital
✨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.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving credit or scorecard modelling. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Practice common data science problems and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by hiring managers.
We think you need these skills to ace Data Scientist - Credit/Scorecard modelling in London - Quant Capital
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, R, and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about data science and how your background in credit/scorecard modelling makes you a perfect fit for our team.
Showcase Your Projects:If you've worked on any models or scorecards that are in production, make sure to mention them! We love seeing real-world applications of your skills, so share those success stories.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any updates from our team!
How to prepare for a job interview at Quant Capital
✨Know Your Models Inside Out
Make sure you can discuss the models and scorecards you've created in detail. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This shows your depth of knowledge and practical experience.
✨Brush Up on SQL and Python/R
Since strong SQL and Python or R skills are essential for this role, practice coding problems and be prepared to demonstrate your proficiency. You might be asked to solve a problem on the spot, so familiarity with these languages is key.
✨Understand Data Warehousing Concepts
Have a solid grasp of data warehousing principles and how they relate to credit scoring. Be ready to discuss how you’ve used data warehousing in your previous projects and how it impacts model performance.
✨Embrace the Company Culture
With an environment likened to Facebook or Google, show that you can fit into a relaxed and open workplace. Prepare to discuss how you collaborate with teams and contribute to a positive work culture, as this will resonate well with the interviewers.
