About this role
Galaxy is seeking a Quantitative Trader (Associate/VP) to join the Onchain Trading team in New York, NY. This technically deep, high-ownership role is ideal for a quantitative professional looking to shape algorithmic strategies, decentralized finance, and protocol-level market structure.
Role Overview
The Quantitative Trader position focuses on the intersection of algorithmic strategy, decentralized finance, and protocol-level market structure. The professional in this role will contribute across the entire trading lifecycle, from designing automated strategies and building risk infrastructure to managing protocol relationships and structuring liquidity agreements.
Key Responsibilities
Requirements
Skills and Tools
Salary and Benefits
About the Company
Galaxy Digital Inc. is a global leader in digital assets and data center infrastructure that connects institutions to digital assets through trading, advisory, asset management, staking, self-custody, and tokenization. Headquartered in New York City with international offices, Galaxy fosters a culture of builders and overachievers who value transparency, independent decision-making, and high performance.
How to Apply
Interested candidates should visit the official Galaxy careers page or website to apply for this position.
Skills and tech stack
Questions candidates ask
What is the location of this job?
This position is located in New York, NY, with hybrid and flexible working arrangements available.
What is the salary range for the Quantitative Trader role?
The base salary ranges from $150,000 to $200,000 USD, supplemented by an annual bonus and equity incentives.
How many years of experience are required?
The company looks for candidates with 2 to 5 years of experience in quantitative trading, systematic strategy research, or algorithmic development.
What programming languages are required?
Solid Python programming skills are required, including experience building data pipelines, backtests, or trading tools.
What educational background is needed?
Candidates must hold a degree in a quantitative field such as Computer Science, Computer Engineering, Applied Mathematics, or Physics.
