Edge-Driven Quant Research Intern (Year-Round)

AXQ Capital, LP.; Northern, New York (KY, NY); Hybrid; USD 103,000 - 138,000; Part time

Job summary

AXQ Capital, LP. is seeking a Quantitative Research Intern for year-round work in New York. The intern will collaborate with senior researchers and portfolio managers on research intended to trade, with strong performers receiving offers for full-time roles.

The role emphasizes development of quantitative trading strategies, data-driven pattern discovery, and the use of machine learning and AI workflows to accelerate backtesting and analysis.

Qualifications

• Undergraduate or graduate student at a top-tier university in a quantitative field (e.g., mathematics, statistics, physics, engineering, computer science, financial engineering)
• Strong foundation in probability and statistics, including statistical modeling, time-series analysis, and machine learning
• Proficient in Python for data analysis and research
• Intellectually curious and quick to learn, with a genuine interest in quantitative finance
• Clear communicator who works well in a team and under pressure

Responsibilities

• Developing and refining quantitative trading strategies under the guidance of experienced portfolio managers and researchers
• Applying tools from probability, statistics, and machine learning to uncover patterns and predictive signals in market data
• Leveraging agentic AI workflows to accelerate the research cycle — from hypothesis generation to automated backtesting and analysis
• Transforming raw, messy datasets into research-ready inputs that power alpha discovery
• Exploring portfolio construction and optimization techniques that combine individual strategies into robust, risk-managed portfolios

Skills

Python

Quantitative finance

Statistics

Team communication

Education

Quantitative field degree

Tools

NumPy

Pandas

Job description

AXQ Capital, LP. is seeking a Quantitative Research Intern for year-round work in New York. The intern will collaborate with senior researchers and portfolio managers on research intended to trade, with strong performers receiving offers for full-time roles.

The role emphasizes development of quantitative trading strategies, data-driven pattern discovery, and the use of machine learning and AI workflows to accelerate backtesting and analysis.