Quantitative Researcher

Neutral Street; New York (NY); On-site; USD 120,000 - 230,000; Full time

Job summary

Neutral Street is seeking a lead quantitative researcher to drive end-to-end strategy development for high-frequency trading in a fast-paced market environment.

You will develop and backtest strategies, analyze massive tick-level data, and build predictive models using advanced statistics and machine learning. Mentoring junior researchers and publishing findings are part of the role.

Qualifications

• Ph.D. or Master’s degree in a highly quantitative field.
• Strong Python (Pandas, NumPy) and C++ programming skills.
• Deep understanding of statistics, ML, and time-series analysis.
• Track record of publishing peer-reviewed research is a plus.

Responsibilities

• Lead development and backtesting of high-frequency trading strategies.
• Analyze tick-level data to uncover microstructure anomalies.
• Build predictive models using advanced statistics and ML techniques.
• Publish internal papers and mentor junior researchers.

Skills

Python (Pandas/NumPy)

C++

Statistics

Machine Learning

Time-series analysis

Backtesting

Education

Ph.D. or Master’s degree in a highly quantitative field

Tools

Pandas

NumPy

Job description

Lead research initiatives to discover new trading signals. You will be responsible for the end-to-end process of strategy development, from initial hypothesis generation to production deployment.

Responsibilities

• Develop and backtest high-frequency trading strategies
• Analyze massive tick-level datasets to uncover market microstructure anomalies
• Build predictive models using advanced statistical and machine learning techniques
• Publish internal research papers and mentor junior researchers

Requirements

• Ph.D. or Master's degree in a highly quantitative field
• Exceptional programming skills in Python (Pandas, NumPy) and C++
• Deep understanding of statistics, machine learning, and time-series analysis
• Track record of publishing peer-reviewed research is a plus