High-Frequency Equity Feature Researcher

I am currently working with a 10bil USD mutli strategy hedge fund on the look out for a highly motivated quantitative researcher to join their equity team and focus on feature engineering for high-frequency equity trading strategies. This role involves working with ultra-low latency data, designing predictive features, and supporting the development of intraday trading models.

Key Responsibilities

• High-Frequency Data Processing

  • Work with tick-level and order book data (e.g., Level 2, market microstructure)
  • Build and maintain pipelines for real-time data ingestion and transformation

• Feature Engineering & Alpha Signal Development

  • Design and evaluate predictive features based on price action, order flow, and liquidity dynamics
  • Apply statistical and machine learning techniques to assess signal quality (e.g., IC, IR, Sharpe)

• Strategy Support & Collaboration

  • Collaborate with PMs and traders to translate features into actionable signals
  • Support intraday and T+0 strategy development with robust feature sets

• Tooling & Infrastructure

  • Contribute to the development of internal feature libraries and research platforms
  • Automate feature testing, decay analysis, and signal combination workflows

Qualifications

• Education

  • Bachelor's or higher degree in Mathematics, Statistics, Computer Science, Financial Engineering, or related fields

• Experience

  • 2+ years of experience in high-frequency equity research or trading
  • Proven track record in feature engineering for intraday strategies
  • Experience with A-share markets is a strong plus

• Technical Skills

  • Proficient in Python (e.g., pandas, numpy, scikit-learn); C++ experience is a plus
  • Familiarity with low-latency data processing and real-time systems
  • Solid understanding of machine learning and statistical modeling

• Soft Skills

  • Strong analytical thinking and problem-solving ability
  • Effective communication and collaboration across quant, trading, and engineering teams
  • Passion for high-frequency trading and data-driven research
  • Mandarin speaking

Bonus Points

• Experience building high-frequency factor libraries or feature platforms
• Familiarity with microstructure modeling and order book dynamics
• Competitive programming or academic research background
• Prior experience at HFT firms or hedge funds