Quantitative Arbitrage Trader Proprietary Desk

5 - 9 years

0 Lacs

Posted:2 weeks ago| Platform: Shine logo

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On-site

Job Type

Full Time

Job Description

Role Overview: You will be joining as an Arbitrage Trader with expertise in quantitative trading to work on identifying and executing high-probability arbitrage opportunities across markets by leveraging data, technology, and statistical methods. As part of the team, you will have the freedom to innovate, develop trading strategies, and work in a performance-driven environment with advanced infrastructure and capital support. Key Responsibilities: - Design, develop, and manage quantitative arbitrage strategies for various asset classes. - Identify and exploit market inefficiencies and pricing anomalies using automated and semi-automated strategies. - Enhance strategy performance through statistical analysis, back-testing, and real-time monitoring. - Manage risks by overseeing position sizing, exposure monitoring, and performance attribution. - Keep abreast of market structure changes, regulatory updates, and technological advancements affecting trading efficiency. Qualifications Required: - Proven experience in quantitative arbitrage trading at a proprietary desk, hedge fund, or HFT setup. - Proficiency in quantitative models, market micro-structure, and statistical methods. - Hands-on experience with Python (preferred), R, C++, or similar languages for strategy development and automation. - Ability to analyze large datasets, derive actionable insights, and construct logic-driven trading frameworks. - Understanding of risk control techniques and real-time risk monitoring. - Capable of making rational decisions swiftly in high-stakes market scenarios. - Ability to maintain composure during volatile market conditions. - Willingness to learn, adapt, and refine strategies according to market dynamics. - Familiarity with trading platforms, APIs, market data systems, and low-latency environments. - Comfortable collaborating in cross-functional teams with developers, researchers, and risk professionals. - Bachelor's or Master's degree in Finance, Economics, Mathematics, Statistics, Engineering, Computer Science, or related field. - Advanced qualifications such as CFQ, FRM, CMT are a plus.,

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