Quantitative Trading Intern - 2026 Summer Internship, Hong Kong at Galaxy

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

17 Feb, 26

Salary

0.0

Posted On

19 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistics, Probability, Time-Series Modeling, Systematic Trading, Python, Pandas, NumPy, SciPy, Data Engineering, Market Microstructure, Communication, Collaboration, Research, Hypothesis Validation, Experiment Design

Industry

Financial Services

Description

Who We Are: Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality. Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S. We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI. Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. To learn more about our businesses and products, visit www.galaxy.com. What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. About the Galaxy Summer Internship Program: The Galaxy HK Summer Internship Program is an immersive and exciting, nine-week experience taking place on-site in our Hong Kong office. During the nine weeks, you will have the opportunity to gain hands-on, practical work experience across our teams. In addition to learning on the job, Galaxy interns participate in professional development programming, fun social events, and networking opportunities with senior leaders. We will be looking for 5 individuals for our program, and each intern will be allocated to one of the following teams: Sales, Quant Trading, Derivatives Trading, Risk and Lending. Program Dates: June to August 2026 What you’ll do as a Quantitative Trading intern: Support the research and iteration of the desk's systematic trading strategies and frameworks Clean, analyze, and model large historical datasets to identify predictive signals and evaluate their robustness Assist in refining the desk’s backtesting framework, including performance analytics, risk decomposition, and scenario testing Help improve and maintain data pipelines, research tooling, and model monitoring dashboards Collaborate with traders and researchers to assess execution quality, slippage patterns, and potential workflow enhancements Summarize research findings and propose strategy improvements or new hypotheses to the team in a clear, structured manner What We’re Looking For: Solid understanding of statistics, probability, and time-series modeling, with interest in systematic trading Strong Python skills (Pandas, NumPy, SciPy) and comfort working with large, noisy real-world datasets Ability to design clean research experiments, validate hypotheses, and recognize common pitfalls like regime shifts and overfitting Strong communication and collaboration skills, with the ability to present complex ideas clearly Self-directed, curious, and comfortable working in a fast-paced, iterative research workflow Familiarity data engineering basics and market microstructure concepts is a plus, but not required Eligibility Requirements: Undergraduate or master’s students graduating between December 2026 and June 2027 Eligible master’s students must have fewer than two years of relevant, full-time work experience Students enrolled in PhD, MBA, or JD programs are not eligible to apply. What We Offer: Competitive intern salary Free virtual coaching sessions through Headspace Free daily snacks in-office and Monday lunches Opportunities to learn about the Crypto industry Smart, entrepreneurial, and fun colleagues *Benefits may vary based on location. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.

Responsibilities

As a Quantitative Trading intern, you will support the research and iteration of systematic trading strategies and frameworks. You will also analyze large datasets to identify predictive signals and assist in refining backtesting frameworks.