At a Glance
- Tasks: Create impactful credit models and scorecards using advanced data techniques.
- Company: Join a relaxed, innovative environment like Facebook or Google.
- Benefits: Enjoy competitive compensation and a vibrant work culture.
- Other info: Full-time role with excellent growth potential in a dynamic team.
- Why this job: Make a real difference in the financial sector with your data skills.
- Qualifications: Strong experience in SQL, Python or R, and data warehousing.
The predicted salary is between 50000 - 70000 € per year.
Data Scientist - Credit/Scorecard modelling in London, United Kingdom
Posted about 1 year ago
Tech stack:
- Python
- R
- Tooling
- 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 eager 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 current or former employees at Quant Capital on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and scorecards. Use GitHub to share your projects, and make sure to highlight your Python and SQL prowess.
✨Tip Number 3
Prepare for the interview by brushing up on AI tooling and data warehousing concepts. We want to impress them with our knowledge and confidence in these areas!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can keep track of your progress and offer support along the way.
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 model/scorecard creation experience!
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 fits into our relaxed and open work environment. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! We love seeing practical applications of your skills, especially in credit or scorecard modelling. Include links if possible!
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 important updates from us!
How to prepare for a job interview at Quant Capital
✨Know Your Tech Stack
Make sure you’re well-versed in Python, R, and SQL. Brush up on your experience with AI tooling and data warehousing, as these are crucial for the role. Be ready to discuss specific projects where you've applied these skills.
✨Showcase Your Modelling Experience
Prepare to talk about your experience creating models and scorecards. Have examples ready that demonstrate how your models have been used in production. This will show your practical understanding of the role and its requirements.
✨Understand the Company Culture
Since the work environment is relaxed and open, be yourself during the interview. Show your personality and how you can fit into a culture similar to Facebook or Google. This can help you stand out as a candidate who would thrive in their setting.
✨Ask Insightful Questions
Prepare thoughtful questions about the team, projects, and future challenges they face. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals.
