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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.
If this opportunity aligns with your career aspirations, we encourage you to apply and explore the potential for growth and unparalleled success.
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
Network with professionals in the hedge fund industry, especially those who specialise in quantitative research. Attend relevant conferences or webinars to meet potential colleagues and learn about the latest trends in statistical arbitrage.
✨Tip Number 2
Showcase your programming skills by contributing to open-source projects or creating your own projects that demonstrate your expertise in Python, R, or C++. This will not only enhance your portfolio but also provide you with practical experience that can impress hiring managers.
✨Tip Number 3
Stay updated on the latest academic research and advancements in quantitative finance. Reading recent papers and implementing new techniques can give you an edge in interviews, as it shows your commitment to continuous learning and innovation.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving and coding challenges related to statistical arbitrage. Familiarise yourself with common algorithms and data structures, as well as machine learning techniques, to demonstrate your analytical skills effectively.
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. Include specific examples of your work with trading models and any programming languages you are proficient in, such as Python or R.
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 how your background aligns with the firm's culture of collaboration and excellence.
Showcase Your Achievements: Provide concrete examples of your accomplishments in previous roles, particularly those that demonstrate your ability to develop and implement successful trading strategies. Highlight any use of machine learning techniques in your work.
Prepare for Technical Questions: Anticipate technical questions related to quantitative finance and statistical methods during the interview process. Brush up on your knowledge of market microstructure and be ready to discuss how you would approach developing new trading models.
How to prepare for a job interview at Onyx Alpha Partners
✨Showcase Your Quantitative Skills
Be prepared to discuss your quantitative skills in detail. Highlight specific projects or models you've developed, especially those related to medium frequency statistical arbitrage. Use clear examples to demonstrate your analytical thinking and problem-solving abilities.
✨Familiarise Yourself with Market Microstructure
Understand the fundamentals of market microstructure as it relates to statistical arbitrage. Be ready to discuss how you would integrate new strategies into existing portfolios and how market conditions can affect trading algorithms.
✨Demonstrate Programming Proficiency
Since strong programming skills are essential for this role, be prepared to discuss your experience with Python, R, or C++. You might even be asked to solve a coding problem during the interview, so brush up on your coding skills and relevant libraries like TensorFlow or scikit-learn.
✨Emphasise Collaboration and Communication
Given the firm's collaborative culture, highlight your ability to work well in teams. Share examples of how you've successfully collaborated with portfolio managers or other researchers to develop trading strategies, and express your enthusiasm for open dialogue and sharing ideas.
