High Frequency Quantitative Researcher

Client: NYC

Specific: Fully Systematic Trading Firm

Project: Full-Time

Compensation: Base + Bonus

We are seeking a highly skilled and motivated Quantitative Equities High Frequency Trading Researcher to join a talented team of researchers and traders. As a key member of the research division, you will be responsible for developing, testing, and implementing quantitative trading strategies with a focus on high frequency trading in equity markets. The successful candidate will demonstrate a deep understanding of financial markets, statistical analysis, and algorithmic trading.

Responsibilities (Not Limited to) :

• Develop, backtest, and optimize proprietary trading models and strategies using market microstructure data, historical price data, and other relevant financial datasets.
• Work closely with the technology team to implement and deploy trading algorithms into the firm's high frequency trading infrastructure.
• Optimize and fine-tune trading algorithms to ensure optimal performance and low-latency execution.
• Utilize statistical methods, machine learning techniques, and data visualization tools to validate and improve trading models.
• Analyze large datasets to derive insights into market behavior and identify patterns or anomalies that can be exploited in trading strategies.
• Conduct rigorous quantitative research to identify profitable trading opportunities in equities markets, specifically in high frequency trading.
• Collaborate with team members to generate innovative ideas and hypotheses for enhancing trading performance.
• Stay up-to-date with the latest research developments and industry trends to enhance the team's research capabilities.

Qualifications:

• Strong understanding of market microstructure, order book dynamics, and liquidity.
• Advanced degree (Masters or Ph.D.) in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Physics, or related disciplines.
• Excellent problem-solving skills and a strong analytical mindset.
• Ability to work in a fast-paced, high-pressure environment while maintaining attention to detail.
• Excellent communication skills and the ability to convey complex ideas effectively
• Proficiency in programming languages such as Python, R, C++, or similar for data analysis, modeling, and algorithm development.
• Familiarity with relevant financial databases and data sources (e.g., Bloomberg, FactSet, etc.).
• Experience with data manipulation, statistical analysis, and machine learning techniques for financial data.
• Demonstrated experience in developing and implementing quantitative trading strategies, ideally with a focus on high frequency trading in equities markets.