Responsibilities • Strategy Validation & Back-testing: Conduct rigorous quantitative analysis to verify the validity and reliability of existing investment strategies. Use historical and tick-level data to assess performance under diverse market conditions, identifying potential flaws or optimization opportunities. • Deep Data Insight: Dive deep into large, complex datasets to uncover underlying patterns and relationships. Translate these findings into actionable insights and communicate complex results to both technical teams and non-technical stakeholders. • Technological Innovation: Stay at the forefront of advancements in blockchain, DeFi protocols, and traditional finance. Apply emerging technologies to develop innovative systematic trading ideas, such as integrating smart contracts into automated trading algorithms. • Risk Management & Execution: Actively collaborate with the team to resolve real-time trading and risk management issues. Ensure all information is presented with precision and timeliness to support rapid decision-making in high-pressure environments. • System Optimization: Partner with developers to enhance trading infrastructure, ensuring strategies are executed with minimal latency and high fault tolerance.
Requirements • Educational Excellence: Robust quantitative background, preferably with a Master’s or PhD in Mathematics, Physics, Statistics, Computer Science, or a related field from a top-tier university. • Professional Experience: Proven experience in quantitative trading or portfolio management. Demonstrated ability to analyze market data, develop systematic strategies, and manage multi-asset investment portfolios. • Technical Proficiency: Advanced programming skills in Python (NumPy, Pandas), SQL, and ideally C++ or Rust for high-performance applications. • Blockchain Knowledge: Solid understanding of blockchain technology, including smart contract analysis (e.g., Solidity), DeFi mechanisms (DEXs, lending protocols), and on-chain data analysis. • Analytical Rigor: Strong foundation in probability, statistics, and machine learning techniques. • Proven Track Record: Proof of a successful tracking record in live trading environments is highly advantageous.