Responsibilities

📍Strategy Development:Design and optimize quantitative trading strategies using statistical modeling, machine learning, and data-driven insights across digital asset markets. 📍Market Signal Research:Analyze large-scale datasets—including order book, tick-level, on-chain, and macroeconomic data—to identify predictive signals and alpha opportunities. 📍Backtesting & Simulation:Build and enhance robust backtesting frameworks to validate trading hypotheses under various market conditions and stress scenarios. 📍Execution Optimization:Collaborate with developers to integrate predictive models into low-latency trading systems and continuously improve execution performance. 📍Portfolio Analytics:Conduct post-trade analysis, PnL decomposition, and contribute to systematic portfolio optimization initiatives.

Requirements

📍Bachelor’s, Master’s, or PhD in Computer Science, Applied Math, Statistics, or related fields. 📍3+ years (mid-level) or 6+ years (senior) of experience in algorithmic or quantitative trading. 📍Solid background in Python (NumPy, pandas, scikit-learn, PyTorch) and/or C++ for performance-critical components. 📍Experience working with market microstructure data, including order books and tick-level data. 📍Strong foundation in probability theory, time-series modeling, and optimization. 📍Bonus: Experience with kdb+/q, columnar/time-series databases, or high-frequency trading systems. Bonus: Familiarity with crypto market structure, DEX/CEX dynamics, and derivatives trading. 📍Excellent communication and documentation skills; Self-driven, curious, and passionate about building scalable trading systems with impact.

Looking for your next challenge? The world of crypto offers exciting roles in blockchain development, web3 innovations, and remote opportunities.