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- Tasks: Support risk model development through quantitative research and back-testing.
- Company: Leading financial markets organisation with a focus on innovation.
- Benefits: Competitive day rate, flexible working arrangements, and professional growth opportunities.
- Why this job: Join a dynamic team and make an impact in the financial sector.
- Qualifications: PhD or Master’s in a quantitative field with programming skills in Python, R, SQL, and C++.
- Other info: Exciting contract role with potential for career advancement.
A leading financial markets organisation is seeking a Quantitative Risk Analyst to support the development of risk models. The role involves quantitative research, designing back-testing approaches, and validating model performance.
The ideal candidate will have:
- A PhD or Master’s in a quantitative field
- Strong knowledge of derivatives pricing
- Hands-on experience with Python, R, SQL, and C++
- Excellent communication skills
Day rate ranges from £300 to £375, inside IR35.
PhD+ Quantitative Risk Analyst (Contract) – London employer: Kite Consulting Group
Contact Detail:
Kite Consulting Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD+ Quantitative Risk Analyst (Contract) – London
✨Tip Number 1
Network like a pro! Reach out to professionals in the financial markets sector on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Make sure you can confidently discuss derivatives pricing and demonstrate your knowledge of Python, R, SQL, and C++. Practice common interview questions related to quantitative risk analysis.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant research or model development, be ready to discuss it in detail. Use examples that highlight your problem-solving skills and how you validated model performance.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can give you an edge. Plus, it’s a great way to stay updated on new roles that match your skills.
We think you need these skills to ace PhD+ Quantitative Risk Analyst (Contract) – London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in quantitative research and risk modelling. We want to see how your skills in Python, R, SQL, and C++ align with the role, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Quantitative Risk Analyst position. Share specific examples of your past work that demonstrate your expertise in derivatives pricing and model validation.
Show Off Your Communication Skills: Since excellent communication is key for this role, make sure your application reflects that. Keep your language clear and concise, and don’t forget to proofread for any typos or errors before hitting send!
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 about the process!
How to prepare for a job interview at Kite Consulting Group
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative research skills and risk modelling knowledge. Be ready to discuss your experience with derivatives pricing and how you've applied your academic background in real-world scenarios.
✨Show Off Your Coding Skills
Since the role requires hands-on experience with Python, R, SQL, and C++, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to risk analysis beforehand.
✨Communicate Clearly
Excellent communication skills are a must for this position. Practice explaining complex concepts in simple terms, as you may need to present your findings to non-technical stakeholders. Think about examples where you've successfully communicated technical information.
✨Prepare for Back-Testing Questions
Since designing back-testing approaches is part of the job, review your past experiences with back-testing models. Be ready to discuss the methodologies you used, the challenges you faced, and how you validated model performance.
