Quantitative Researcher - Systematic Equities & ML

Alexander Chapman; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Alexander Chapman seeks a Quantitative Researcher to help build a next-generation systematic equities platform. The role spans alpha generation, model development, and research platform evolution in a fast-moving hedge fund environment.

Ideal candidates have strong quantitative training, Python expertise (NumPy/pandas), and interest in financial markets, with independence and initiative to shape research direction.

Qualifications

• Strong academic background in a quantitative discipline, Mathematics, Statistics, Physics, Computer Science, or a related field.
• Excellent Python skills, including NumPy and pandas; experience with ML frameworks is a plus
• Experience in quantitative research, alpha generation, systematic strategies, or machine learning
• Strong understanding of statistics, probability, and data analysis
• Genuine interest in financial markets, with equities experience particularly relevant
• Strong research mindset and the ability to work independently in a fast-moving environment

Responsibilities

• Developing systematic equity strategies and identifying new sources of alpha
• Researching signals across market, fundamental, and alternative datasets
• Applying machine learning and statistical techniques to predictive modeling
• Taking ideas from initial research through to robust, scalable strategies
• Improving model performance, robustness, and scalability

Skills

Quantitative research

Statistical analysis

Independent work

Education

Quantitative discipline degree

Tools

Python (NumPy, pandas)

ML frameworks

Job description

Alexander Chapman seeks a Quantitative Researcher to help build a next-generation systematic equities platform. The role spans alpha generation, model development, and research platform evolution in a fast-moving hedge fund environment.

Ideal candidates have strong quantitative training, Python expertise (NumPy/pandas), and interest in financial markets, with independence and initiative to shape research direction.