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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 48000 - 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
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 skills but also provide tangible 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. 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 the hedge fund environment. Mention how your background aligns with the firm's focus on innovation and collaboration, and provide examples of your past successes in developing trading strategies.
Showcase Your Technical Skills: Be explicit about your programming skills and experience with machine learning libraries. If you have worked on projects involving predictive analytics, make sure to detail these experiences, as they are crucial for this role.
Highlight Academic Achievements: If you hold a Ph.D. or have notable academic accomplishments, ensure these are prominently featured in your application. Discuss any relevant research that demonstrates your expertise in quantitative fields and how it applies to the role.
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 concrete examples to demonstrate your expertise in developing and refining 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 projects where you utilised Machine Learning libraries like TensorFlow or scikit-learn, and be prepared for technical questions or coding challenges.
✨Understand Market Microstructure
Familiarise yourself with market microstructure concepts as they are essential for the role. Be ready to discuss how you would integrate new strategies into existing portfolios and how you monitor market conditions to adjust algorithms effectively.
✨Emphasise Collaboration and Communication
The firm values a collaborative culture, so highlight your ability to work well in teams. Share experiences where you successfully collaborated with portfolio managers or other researchers, and how open dialogue led to innovative trading strategies.
