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- Tasks: Calibrate volatility surfaces and design automated algorithms for market analysis.
- Company: Join a modern tech firm with a flat structure and no bureaucracy.
- Benefits: Remote work, flexible hours, health insurance, and support for personal development.
- Why this job: Collaborate with top professionals and make an impact in quantitative research.
- Qualifications: 5+ years in quantitative research, strong coding skills, and a collaborative mindset.
- Other info: Great opportunities for growth and working with industry leaders.
The predicted salary is between 54000 - 84000 £ per year.
Calibrate SSVI or similar volatility surfaces using market data to ensure smoothness, arbitrage-free conditions, and temporal stability;
Design and implement automated algorithms for adjusting surface parameters such as skew, curvature, and wing dynamics;
Tune and debug models under realistic market conditions – including bid/ask spreads, market noise, and incomplete markets;
Analyze historical and live market data to identify trading opportunities and spread dislocations;
Perform backtests on option spread strategies portfolio optimizations and against multiple underlyings;
Collaborate with the quant team to enhance ML pipelines and expand statistical toolkits for research and production use.
Qualifications
- 5+ years in Quantitative Research / Trading; background in a top-tier proprietary trading firm or hedge fund is strongly preferred;
- Strong experience with basket and portfolio option strategies, including pricing and risk management;
- Proven track record in building inventory-aware models where quoted prices adjust based on live risk metrics and our options position;
- Practical experience with VaR simulations and SPAN margin optimizations;
- Experience supporting systematic trading strategies with holding periods from minutes to several hours, including near-expiry trading (non-latency sensitive);
- Background in single-name equity or equity index options preferred;
- Proficiency in Python, C++, or Rust;
- Solid understanding of market microstructure;
- Strong collaborative spirit, work ethics, and a determined drive for success; ability to work both independently and as part of a team;
- Strong communication skills, with the ability to clearly explain complex ideas.
Additional Information
What we offer: Experience a modern international technology company without the burden of bureaucracy. Collaborate with industry-leading professionals, including former employees of Tower, DRW, Broadridge, Credit Suisse, and more. Enjoy excellent opportunities for professional growth and self-realization. Work remotely from anywhere in the world with a flexible schedule. Receive compensation for health insurance, sports activities, and non-professional training.
Quantitative Researcher, Volatility in London employer: BHFT
Contact Detail:
BHFT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher, Volatility in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who have experience in quantitative research or trading. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past projects or research that highlights your expertise in volatility surfaces and algorithm design. This will give you an edge during interviews and show that you mean business.
✨Tip Number 3
Practice makes perfect! Brush up on your Python, C++, or Rust skills by working on relevant coding challenges or projects. Being able to demonstrate your technical prowess will definitely impress potential employers.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Quantitative Researcher, Volatility in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in quantitative research and trading. We want to see how your skills align with the job description, so don’t be shy about showcasing your background in volatility surfaces and algorithm design!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your experience with market data and option strategies makes you a perfect fit for our team. Keep it engaging and relevant!
Showcase Your Technical Skills: We love seeing technical prowess! Make sure to highlight your proficiency in Python, C++, or Rust, and any experience you have with VaR simulations or portfolio optimisations. This will help us understand your capabilities right off the bat.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at BHFT
✨Know Your Volatility Surfaces
Make sure you brush up on calibrating SSVI and similar volatility surfaces. Be ready to discuss how you ensure smoothness and arbitrage-free conditions using market data. Having specific examples from your past experience will show that you know your stuff!
✨Show Off Your Coding Skills
Since proficiency in Python, C++, or Rust is key, be prepared to talk about your experience with automated algorithms. Maybe even bring a small project or code snippet to demonstrate your skills. This will help us see your practical knowledge in action.
✨Discuss Real Market Conditions
Be ready to dive into how you've tuned and debugged models under realistic market conditions. Discussing your approach to handling bid/ask spreads and market noise will highlight your understanding of the complexities involved in quantitative research.
✨Collaboration is Key
We value a strong collaborative spirit, so think of examples where you've worked with a team to enhance ML pipelines or expand statistical toolkits. Show us how you communicate complex ideas clearly, as this is crucial for success in our environment.
