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- Tasks: Develop and refine innovative trading models for medium frequency statistical arbitrage.
- Company: Join a leading hedge fund with $30 billion in assets, known for excellence and innovation.
- Benefits: Enjoy a collaborative culture, cutting-edge technology, and opportunities for professional growth.
- Why this job: Be part of an elite team where your ideas can directly impact trading strategies and success.
- Qualifications: Ph.D. in a quantitative field and 3+ years of experience in quantitative research required.
- Other info: Strong programming skills in Python, R, or C++ are essential; ethical standards are a must.
The predicted salary is between 54000 - 84000 £ per year.
A leading multi-strategy hedge fund with ~$30 billion in assets under management is seeking an exceptional Medium Frequency Statistical Arbitrage Quant Researcher. With a global footprint and a reputation for excellence, our client employs state-of-the-art technology and data-driven methodologies to achieve superior returns across various asset classes.
The firm is built on a foundation of meritocracy, attracting and retaining the industry's leading quants and portfolio managers. They value intellectual curiosity, collaboration, and a commitment to excellence. The collaborative culture encourages open dialogue about the dynamic and rapidly changing environment, where information flows freely and novel ideas are transformed into actionable trading strategies.
We are actively looking for a Quant Researcher specialized in Medium Frequency Statistical Arbitrage strategies to work for a high profile trading pod with an exceptional track record. As a key member of this elite research team, you will have the opportunity to apply your astute quantitative skills to develop and refine trading models that are both innovative and profitable.
Key Responsibilities:- Design and implement medium frequency statistical arbitrage strategies across various markets from end to end.
- Optimize the way in which the team extracts maximum value from signals, and backtesting to evaluate the performance of trading models.
- Collaborate with portfolio managers to integrate new market microstructure strategies into the existing portfolio.
- Continuously monitor market conditions to adjust parameters and algorithms accordingly.
- Maintain a strong understanding of academic research to keep the team updated with the latest quantitative techniques and theories.
- Preferably a Ph.D. in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Computational Finance.
- Evidence of exemplary accomplishments either in academia or industry.
- A minimum of 3 years of experience in quantitative research, within a multi-strategy hedge fund environment.
- Strong programming skills in Python, R, or C++, with a focus on Machine Learning libraries such as TensorFlow or scikit-learn.
- Demonstrated success in developing and trading medium frequency statistical arbitrage strategies, with examples of applying Machine Learning techniques for predictive analytics.
- Exceptional analytical skills, with a focus on data-driven decision-making.
- High ethical standards and a commitment to maintaining the firm's reputation for integrity.
At Onyx Alpha Partners, we are committed to connecting the most sought after talent in the financial world, to opportunities that expand the universe of unconstrained performance within their chosen discipline. If this opportunity aligns with your career aspirations, we encourage you to apply and explore the potential for growth and unparalleled success.
Locations
Statistical Arbitrage Quant Researcher employer: Onyx Alpha Partners
Contact Detail:
Onyx Alpha Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Statistical Arbitrage Quant Researcher
✨Tip Number 1
Familiarise yourself with the latest trends in statistical arbitrage and quantitative finance. Read up on recent academic papers and industry reports to demonstrate your knowledge during interviews.
✨Tip Number 2
Network with professionals in the hedge fund space, especially those who focus on quantitative research. Attend industry conferences or webinars to make connections that could lead to referrals.
✨Tip Number 3
Showcase your programming skills by working on personal projects or contributing to open-source initiatives. This will not only enhance your portfolio but also provide concrete examples of your capabilities.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving and coding challenges related to statistical models and machine learning. Use platforms like LeetCode or HackerRank to sharpen your skills.
We think you need these skills to ace Statistical Arbitrage Quant Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quantitative skills and relevant experience in statistical arbitrage. Emphasise your programming proficiency in Python, R, or C++, and any experience with Machine Learning libraries.
Craft a Compelling Cover Letter: In your cover letter, express your passion for quantitative research and your understanding of medium frequency statistical arbitrage strategies. Mention specific examples of your past work that demonstrate your analytical skills and success in developing trading models.
Showcase Your Academic Achievements: If you have a Ph.D. or other relevant academic qualifications, make sure to include them prominently. Highlight any publications or research projects that relate to quantitative finance or statistical methods.
Prepare for Technical Questions: Be ready to discuss your previous projects and the methodologies you used. Prepare to explain your approach to backtesting and optimising trading strategies, as well as how you stay updated with the latest quantitative techniques.
How to prepare for a job interview at Onyx Alpha Partners
✨Showcase Your Quantitative Skills
Be prepared to discuss your quantitative background in detail. Highlight specific projects or research you've conducted, especially those related to statistical arbitrage. Use examples that demonstrate your ability to develop and refine trading models.
✨Demonstrate Programming Proficiency
Since strong programming skills are crucial for this role, be ready to talk about your experience with Python, R, or C++. Discuss any relevant Machine Learning libraries you've used, such as TensorFlow or scikit-learn, and how they contributed to your previous work.
✨Understand Market Microstructure
Familiarise yourself with market microstructure concepts, as you'll need to collaborate with portfolio managers on integrating new strategies. Be prepared to discuss how you would approach adjusting parameters and algorithms based on changing market conditions.
✨Emphasise Collaboration and Communication
The firm values a collaborative culture, so highlight your experience working in teams. Share examples of how you've effectively communicated complex ideas and collaborated with others to achieve common goals in your previous roles.
