InfiniteQuant is a global quantitative trading and technology company. As a privately owned and funded proprietary trading firm, we focus on high-frequency quantitative trading across global financial markets. Everything from data to strategy, simulation, and trading systems is developed in-house.
Role
- Research, design, and deploy new algorithmic trading strategies for digital assets, forex, or commodities markets
- Take full responsibility for the strategy lifecycle, from idea generation and research to simulation and live production
- Iterate on strategy behavior and performance in live markets
- Build a deep understanding of market microstructure through hands-on production trading
Program Structure
- Designed for experienced traders with an existing strategy or experienced researchers who have not yet scaled a fully independent strategy
- Provides a structured path toward independent strategy ownership and progression to Trading Pod Lead
- Includes training, technical review, and ongoing advisory support from senior traders and system owners
We Provide
- In-house data, simulation, and low-latency trading platforms
- Proprietary trading infrastructure and internal capital
- Direct market access to global exchanges with institutional connectivity
- Training, mentorship, and advisory support from senior traders
- Master or Ph.D. degree in STEM (Science, Technology, Engineering, and Mathematics)
- Prior work experience in high frequency trading firms or hedge funds
- Prior experience developing or operating fully automated quantitative trading strategies
- C++ / Python experience
- Solid understanding of market microstructure and execution
- High-ownership, self-directed, systems-oriented mindset
Job description provided by InfiniteQuant.
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