Editorial summary

The company, a leading fintech firm specializing in systematic and quantitative investment strategies for global hedge funds, is seeking a Quant Developer (Python) Intern. The role involves developing quantitative models and trading strategies using large-scale financial data, as well as conducting research in machine learning, reinforcement learning, and statistical arbitrage. Ideal candidates are highly motivated students or recent graduates with a passion for quantitative finance and financial markets. The internship offers a monthly stipend of 1800.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job id 16756 first appeared in Job-Q.com on 26 Jun 2026]

We are a leading fintech company focused on developing systematic and quantitative investment strategies for global hedge funds, covering both USD- and RMB-denominated products. We are seeking highly motivated students and fresh graduates who are passionate about quantitative finance, machine learning, and financial markets.

Key Responsibilities

• Assist in developing quantitative models and trading strategies based on large-scale financial datasets.
• Conduct research on machine learning, reinforcement learning, quantitative modeling, and statistical arbitrage strategies.
• Analyze and process market data across multiple asset classes, including futures and U.S. equities.
• Support backtesting, strategy evaluation, and performance optimization.
• Participate in quantitative research and development using Python and/or C++.
• Collaborate with senior researchers and portfolio managers on strategy research projects.

Requirements

• Undergraduate, Master's student in Computer Science, Mathematics, Statistics, Finance, Physics, Engineering, or related quantitative disciplines.
• Strong interest in quantitative finance, algorithmic trading, machine learning, or reinforcement learning.
• Proficient in Python; familiarity with C++ is a plus.
• Solid foundation in mathematics, statistics, data analysis, and programming.
• Strong analytical and problem-solving skills with attention to detail.
• Good communication skills and ability to work effectively in a team environment.
• Previous experience in quantitative research, machine learning projects, trading competitions, or related internships is advantageous.

Preferred Qualifications

• Experience with machine learning, reinforcement learning, time-series analysis, or quantitative modeling.
• Familiarity with financial markets, futures, equities, or derivatives.
• Experience in high-frequency trading research, statistical arbitrage, or factor modeling is a plus.
• Publications, competition awards, or open-source project contributions are highly regarded.

What We Offer

• Hands-on exposure to real-world quantitative trading and hedge fund strategies.
• Mentorship from experienced quantitative researchers and portfolio managers.
• Opportunity to work with cutting-edge machine learning and reinforcement learning techniques.

We invite qualified candidates to submit their resumes to: alice@morganfund.com

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