Responsibilities 1. Own the architecture and optimization of the order execution layer for the firm’s high-frequency market-making, arbitrage, and short-cycle strategies, including but not limited to order slicing, order placement algorithms, cancellation logic, Smart Order Routing, and cross-exchange matching. 2. Conduct in-depth analysis of exchange and trading-pair microstructure characteristics (order-book depth, order-book dynamics, matching priority, maker-taker fee structures, latency distributions) and translate findings into actionable strategy adjustments. 3. Design, develop, and implement execution algorithms (e.g., TWAP, VWAP, POV, iceberg orders, dynamic pegged/passive-aggressive hybrid strategies) to maximize fill efficiency and minimize slippage and market impact. 4. Monitor execution quality, slippage, market impact, hedging latency, and execution costs in real time (including trading fees, funding rates, cancellation costs, cross-exchange fund-transfer times, etc.), and produce regular TCA (Transaction Cost Analysis) reports to drive continuous improvement. 5. Collaborate closely with the quantitative research and quant-development teams to deploy alpha signals at the execution layer, optimizing system latency, throughput, and robustness. 6. Build and maintain comprehensive monitoring and alerting for the execution system, enabling rapid response and failover in the event of API latency spikes, liquidity shocks, exchange outages, or cross-exchange fund-transfer delays. 7. In a crypto context, optimize routing strategies across multiple exchanges and product types (spot/perpetual). 8. Continuously research market structure evolution (centralized-exchange changes, algorithmic counterparty behavior) and integrate new insights into execution strategies. Requirements 1. Bachelor’s degree or higher in Mathematics, Statistics, Computer Science, Physics, Financial Engineering, or a related quantitative discipline; Master’s or above preferred. 2. Proven programming skills in at least one language (Python, C++, Rust, Go, etc.) for algorithm implementation, data analysis, and API integration. 3. Deep understanding of market microstructure, order-book matching mechanisms, liquidity theory, price impact, and transaction-cost models; prior HFT or high-frequency execution experience is a plus. 4. Familiarity with crypto exchanges/products (spot, perpetual swaps, options, DeFi/DEX pools) and their execution characteristics (API design, passive/active order behavior, funding rates, cross-exchange latency, etc.). 5. Hands-on experience designing and optimizing HFT or market-making, arbitrage, and execution algorithms; able to measure slippage, impact, and latency in live trading and recommend improvements. 6. Proficiency with data-analysis and backtesting tools (pandas, NumPy, SciPy, matplotlib, or specialized HFT toolkits) and skill in extracting statistical features from tick-level data. 7. Strong teamwork and communication skills, with the ability to collaborate effectively with research, development, trading, and risk-management teams; high execution drive and rapid response to trading-execution incidents. 8. Good English reading proficiency, with the ability to comprehend technical and financial literature. Preferred Qualifications 1. Production-level execution experience in multi-exchange, high-frequency trading environments (especially crypto exchanges). 2. Expertise in C++ or Rust and hands-on experience with low-latency system design. 3. Experience in cross-exchange arbitrage, fund pre-positioning, cross-chain transfers, or DEX market making. 4. Understanding of MEV or cryptoeconomic mechanisms and/or relevant research background. 5. Published or internally deployed quantitative/execution research (e.g., market-impact models, microstructure analyses, TCA reports). 6. Direct P&L responsibility in hedging, market making, or trading roles.