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- Tasks: Join our team to research and develop trading strategies across global markets.
- Company: Be part of a dynamic firm specializing in systematic trading and financial services.
- Benefits: Enjoy a full-time role with opportunities for growth and collaboration in a fast-paced environment.
- Why this job: Make an impact by optimizing trading strategies and enhancing risk-adjusted returns using cutting-edge techniques.
- Qualifications: Advanced degree in a quantitative field and 1+ years in systematic trading required.
- Other info: Strong programming skills in Python or C++ are essential for success in this role.
The predicted salary is between 48000 - 84000 £ per year.
Mid/Low Frequency Quantitative Researcher – Systematic Trading
We are seeking a highly skilled Quantitative Researcher to join a systematic trading team, focusing on mid- and low-frequency strategies across global markets. The ideal candidate will have a strong background in statistical modeling, signal generation, and portfolio optimization, with a hands-on approach to research and implementation.
Responsibilities:
- Conduct research on alpha signals, market inefficiencies, and risk premia across equities, futures, and other asset classes.
- Develop and implement mid- and low-frequency trading strategies, balancing predictive power and execution costs.
- Work closely with portfolio managers and developers to integrate strategies into the trading pipeline.
- Utilize statistical and machine learning techniques to refine signal generation and risk management.
- Backtest and validate strategies using large-scale historical and real-time data.
- Optimize portfolio construction techniques to enhance risk-adjusted returns.
Requirements:
- Advanced degree (MSc/PhD) in a quantitative field such as Mathematics, Statistics, Computer Science, or Financial Engineering.
- 1+ years of experience in systematic trading, ideally focusing on mid/low-frequency strategies.
- Strong programming skills in Python and/or C++, with experience working in a research-driven environment.
- Deep understanding of statistical analysis, econometrics, and machine learning applied to financial markets.
- Hands-on experience with large-scale financial data, time-series modeling, and predictive analytics.
- Knowledge of market microstructure and execution strategies is a plus.
- Ability to work in a fast-paced, collaborative environment with strong attention to detail.
Seniority level
Not Applicable
Employment type
Full-time
Job function
Finance
Industries
Financial Services and Software Development
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Quantitative Researcher employer: Radley James
Contact Detail:
Radley James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher
✨Tip Number 1
Make sure to showcase your hands-on experience with statistical modeling and signal generation. Highlight any specific projects or research you've conducted that demonstrate your ability to develop and implement trading strategies.
✨Tip Number 2
Familiarize yourself with the latest trends in mid- and low-frequency trading strategies. Being able to discuss current market inefficiencies and risk premia will show that you're not only knowledgeable but also passionate about the field.
✨Tip Number 3
Network with professionals in the systematic trading space. Attend relevant conferences or webinars, and connect with people on platforms like LinkedIn to gain insights and potentially get referrals.
✨Tip Number 4
Brush up on your programming skills, especially in Python and C++. Be prepared to discuss how you've used these languages in past projects, particularly in relation to backtesting and validating trading strategies.
We think you need these skills to ace Quantitative Researcher
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in systematic trading and any specific projects related to mid- and low-frequency strategies. Use concrete examples to demonstrate your skills in statistical modeling and signal generation.
Showcase Technical Skills: Clearly outline your programming skills, especially in Python and C++. Mention any relevant tools or libraries you have used in your research and how they contributed to your projects.
Demonstrate Analytical Abilities: Discuss your understanding of statistical analysis, econometrics, and machine learning. Provide examples of how you've applied these techniques to financial markets, particularly in backtesting and validating trading strategies.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Address the specific responsibilities and requirements mentioned, showing that you are a perfect fit for the role and the team.
How to prepare for a job interview at Radley James
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python and/or C++. Highlight specific projects or experiences where you applied these skills in a research-driven environment, especially related to systematic trading.
✨Demonstrate Your Understanding of Statistical Techniques
Since the role requires a deep understanding of statistical analysis and machine learning, be ready to explain how you've applied these techniques in financial markets. Use examples from your past work to illustrate your expertise.
✨Discuss Your Research Methodology
Prepare to talk about your approach to conducting research on alpha signals and market inefficiencies. Discuss any specific methodologies you've used for backtesting and validating strategies with large-scale data.
✨Emphasize Collaboration Experience
This position involves working closely with portfolio managers and developers. Share examples of how you've successfully collaborated in a team setting, focusing on communication and integration of strategies into a trading pipeline.
