Quantitative Research Intern (Summer 2027)

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

Job summary

AXQ Capital, a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong, offers a Summer 2027 Quantitative Research Internship in New York. You will work with senior researchers and portfolio managers on research intended to trade, with strong performers receiving full-time offers.

This 12-week internship is based in our New York office, targeting candidates graduating in 2027 or 2028.

Qualifications

• Undergraduate or graduate student in a quantitative field with strong foundations in probability and statistics.
• Proficiency in Python for data analysis and research is required.
• Ability to learn quickly and work well in a team under pressure.

Responsibilities

• Develop and refine quantitative trading strategies under guidance from senior researchers and portfolio managers.
• Apply probability, statistics, and machine learning to uncover patterns and signals in market data.
• Leverage AI workflows to accelerate research from hypothesis to backtesting and analysis.
• Transform raw datasets into research-ready inputs for alpha discovery.
• Explore portfolio construction and optimization techniques for robust risk-managed results.

Skills

Python

Statistics

Time-series analysis

Machine Learning

Communication

Education

Quantitative field student

Tools

Pandas

NumPy

Job description

About Us

AXQ Capital i s a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong. We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

We are growing quickly, and our interns are a core part of how we hire: you will work directly with senior researchers and portfolio managers on research that is meant to trade, and strong performers receive full-time offers.

Job Duties

Markets are noisy, competitive, and constantly evolving — finding a durable edge is one of the hardest problems in applied research. As a Quantitative Research Intern, you will take on that challenge directly. Over the course of your internship, you will work on one or two projects in areas such as:

• 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

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

We'd Love It If You Have

• Publications in leading academic journals or conferences
• Strong results in national or international Olympiads (math, physics, or computer science)

Program Details

This is a full-time, approximately 12-week internship based in our New York office during Summer 2027. We are targeting candidates graduating in 2027 or 2028. The internship concludes with a presentation to senior management and the opportunity to earn a full-time return offer.

The anticipated hourly pay range for this role is $75 to $100, depending on prior experience and qualifications.