Quantitative Developer - Python/Java

<p><p><b>Quantitative Developer :</b><br/><br/>A Quantitative Developer, often called a "Quant Dev," is a highly specialized professional who works at the intersection of finance, mathematics, and computer science.<br/><br/> This role involves designing, implementing, and optimizing algorithms and software solutions for complex financial problems, such as trading strategies, risk management, and pricing models.<br/><br/> A successful Quant Dev combines deep programming expertise with a strong grasp of quantitative finance Responsibilities :</b></p><p><br/></p>- Develop, implement, and maintain complex quantitative models and algorithms for high-frequency trading, risk management, or portfolio optimization.<br/><br/></p><p>- Write high-performance, low-latency code in languages like C++ or Java to ensure real-time system efficiency.<br/><br/></p><p>- Collaborate closely with quantitative researchers, traders, and other stakeholders to translate mathematical models into production-level code.<br/><br/></p><p>- Design and build data pipelines for efficient data acquisition, cleaning, and processing from various financial market sources.<br/><br/></p><p>- Conduct thorough backtesting and validation of models to ensure accuracy and reliability under various market conditions.<br/><br/></p><p>- Optimize and refactor existing codebases to improve performance, scalability, and security.<br/><br/></p><p>- Utilize statistical analysis and machine learning techniques to extract actionable insights from large datasets.<br/><br/></p><p>- Participate in code reviews, system design discussions, and contribute to the team's knowledge Skills & Qualifications :</b></p><p><br/></p>- Master's or Ph.D. in a highly quantitative field such as Computer Science, Mathematics, Physics, or Financial Engineering.<br/><br/></p><p>- Exceptional programming skills in a high-performance language, preferably C++ or Java.<br/><br/></p><p>- Proficiency in Python for prototyping and data analysis is also essential.<br/><br/></p><p>- Strong understanding of data structures, algorithms, and computational complexity.<br/><br/></p><p>- In-depth knowledge of financial markets, instruments (derivatives, equities, etc.), and quantitative finance concepts.<br/><br/></p><p>- Experience with multi-threaded programming and low-latency systems.<br/><br/></p><p>- Familiarity with statistical analysis, machine learning techniques, and relevant libraries (e.g., NumPy, pandas).<br/><br/></p><p>- Experience with large datasets and database systems (SQL, NoSQL).<br/><br/></p><p>- Excellent problem-solving abilities and the capacity to work in a fast-paced, demanding environment.<br/><br/></p><p>- Strong communication skills to explain complex technical concepts to non-technical stakeholders</p><br/></p> (ref:hirist.tech)