Quantitative Research Intern: Build ML-Driven Trading Signals

AXQ Capital, LP.; New York (NY); On-site; USD 103,000 - 138,000; Full time

Job summary

AXQ Capital offers a Quantitative Research Intern position in New York for Summer 2027. The 10-week, full-time internship provides hands-on work with senior researchers and portfolio managers on research intended to trade, with strong performers receiving a full-time offer.

Ideal candidates are PhD students in a quantitative field, proficient in Python, and capable of rapid learning in a collaborative, high-pressure environment.

Qualifications

• PhD student in a quantitative field (e.g., mathematics, statistics, physics, engineering, CS, 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

Probability & statistics

Time-series analysis

Machine learning

Communication

Teamwork

Education

PhD student in quantitative field

Tools

Python

Job description

AXQ Capital offers a Quantitative Research Intern position in New York for Summer 2027. The 10-week, full-time internship provides hands-on work with senior researchers and portfolio managers on research intended to trade, with strong performers receiving a full-time offer.

Ideal candidates are PhD students in a quantitative field, proficient in Python, and capable of rapid learning in a collaborative, high-pressure environment.