Job Description

Description This hybrid role offers a unique opportunity to work across both quantitative development and high-frequency trading. You'll engineer trading systems, design and implement algorithmic strategies, and directly participate in live trading execution and strategy enhancement. Quantitative Strategy & Trading Execution : Design, implement, and optimize quantitative strategies for trading derivatives, index options, and ETFs, Trade across options, equities, and futures, using proprietary HFT platforms Monitor and manage PnL performance, targeting Sharpe ratios of 6+ Stay proactive in identifying market opportunities and inefficiencies in real-time HFT environments Analyze market behavior, particularly in APAC indices, to adjust models and positions dynamically Trading Systems Development : Build and enhance low-latency, high-throughput trading systems Develop tools to simulate trading strategies and access historical market data Design performance-optimized data structures and algorithms for fast execution Implement real-time risk management and performance tracking systems Algorithmic and Quantitative Analysis : Collaborate with researchers and traders to integrate strategies into live environments Use statistical methods and data-driven analysis to validate and refine models Work with large-scale HFT tick data using Python / C++ AI/ML Integration : Develop and train AI/ML models for market prediction, signal detection, and strategy enhancement Analyze large datasets to detect patterns and alpha signals System & Network Optimization : Optimize distributed and concurrent systems for high-transaction throughput Enhance platform performance through network and systems programming Utilize deep knowledge of TCP/UDP and network protocols Collaboration & Mentorship : Collaborate cross-functionally with traders, engineers, and data scientists Represent Dolat in campus recruitment and industry events as a technical mentor What We Are Looking For Strong foundation in data structures, algorithms, and object-oriented programming (C++), python. Experience with AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Hands-on experience in systems programming within a Linux environment. Proficient and Hands on programming using python/ C++ Familiarity with distributed computing and high-concurrency systems. Knowledge of network programming, including TCP/UDP protocols. Strong analytical and problem-solving skills. A passion for technology-driven solutions in the financial markets. (ref:hirist.tech)