Equity Quantitative Researcher

Point72; New York (NY); On-site; USD 80,000 - 120,000; Full time

Job summary

Dormont Manufacturing Co in New York is seeking a skilled researcher to focus on equity market anomalies. You will drive the end-to-end development of alpha strategies, utilizing R or Python, while maintaining portfolio trading.

The ideal candidate has an MS or PhD in a quantitative field and at least 1 year of research experience. A collaborative mindset and strong knowledge of financial markets are essential for success in this role.

Qualifications

• MS or PhD in physics, engineering, statistics, applied math, or quantitative finance required.
• 1+ years of experience in systematic alpha research in equities is needed.
• Experience with short-term alpha signals is advantageous.

Responsibilities

• Conduct innovative research to identify anomalies in equity markets.
• Develop and implement alpha strategies from end to end.
• Scrub, format, and manipulate large data sets efficiently.

Skills

Research in equity markets

Proficiency in R or Python

Applied statistics

Data processing

Financial market knowledge

Education

MS or PhD in quantitative fields

Job description

ROLE/RESPONSIBILITES

• Perform rigorous and innovative research to discover systematic anomalies in equity market
• End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization and production implementation
• Identify and evaluate new datasets for stock return predictions
• Maintain and improve the portfolio trading in production environment

REQUIREMENTS

• MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics
• 1+ years of work experience in systematic alpha research in equities
• Experience developing short term alpha signals (intraday or a few days) is a plus
• Demonstrated proficiency in R or Python
• Strong command of foundations of applied statistics, linear algebra, and time series models
• Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources
• Strong knowledge of financial markets
• Highly motivated, willing to take ownership of his/her work
• Collaborative mindset with strong independent research ability