Quantitative Developer
We're looking for a Quant Developer to sit at the intersection of software engineering and quantitative finance, bridging the gap between research and production. You'll be building the infrastructure that our trading strategies actually run on, including backtesting frameworks, simulation environments, execution systems, and the tooling that lets researchers move from idea to live deployment quickly and with confidence.This role demands both depth and range. You need to write clean, performant, production-ready code, and you need to understand the financial logic behind what you're building well enough to catch problems before they hit live markets. You'll work closely with our quant research team to translate complex mathematical models into reliable systems that execute in real time with minimal latency. If you're the kind of person who takes equal pride in elegant code and sound market intuition, this is built for you.
Responsibilities
- Design and develop backtesting frameworks, research tooling, and simulation environments for quant strategy development
- Implement and maintain trading algorithms and execution systems across live crypto markets
- Optimize code for performance and low latency across the full research-to-production pipeline
- Collaborate directly with quantitative researchers to productionize strategies and ensure research assumptions hold in production
- Build and maintain data pipelines for market data ingestion, processing, and storage
- Monitor and improve live system reliability, catching and resolving issues before they affect trading outcomes
Requirements
- Bachelor's degree or equivalent in Computer Science, Mathematics, Physics, or a related quantitative field
- 3+ years of professional software engineering experience with a focus on performance-critical or financial systems
- Strong proficiency in Python as a primary language, with working knowledge of C++ or another compiled language preferred
- Solid understanding of financial markets, trading concepts, and quantitative methods including time-series analysis and statistical modeling
- Experience building or working with backtesting engines, execution frameworks, or real-time data systems
- Ability to read and reason about mathematical models and translate them into reliable, testable code