Financial Trader

5 days ago

India GoQuant Full time

Quantitative Trading (Paid) - GoQuant Technologies Inc. GoQuant develops solutions that make life easier and more profitable for digital asset traders and researchers. GoMarket is a subscription service that delivers low-latency digital asset data via WebSocket. Features include a unified querying language that allows users to easily bypass exchange-specific protocols to access data. GoTrade is a trade execution platform that allows clients to trade digital assets—using multiple interfaces (Rest API, UI, WebSocket, Redis, etc.) Our infrastructure is built with performance, flexibility, and reliability in mind, leveraging technologies across Python, C++, and cloud-based systems. We are looking for a Quantitative Trader with experience or a strong interest in trading, market microstructure, and quantitative methods. This role will offer hands-on experience with trading strategies, data analysis, and statistical modeling applied to digital asset markets. Quantitative Traders will work closely with other researchers, engineers, and product managers and report directly to the Head of Research. This is a great opportunity to gain practical experience in the fast-paced world of fintech and cryptocurrency trading. Develop and backtest algorithmic trading strategies using quantitative methods. Analyze large datasets across multiple exchanges to uncover patterns and identify trading opportunities. Collaborate with engineers to integrate research into production trading systems. Support the development of risk management and portfolio optimization models. Team Player: We believe in building strong, talented teams. As a Quantitative Trader, you'll have the opportunity to learn from those around you and contribute to a high-performing team. Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Mathematics, Econometrics, Computational Finance, Physics). Strong foundation in mathematics, statistics, or econometrics (e.g., Programming experience in Python, R, MATLAB, or related tools. Familiarity with cryptocurrency markets and trading concepts. Experience with data libraries such as pandas, numpy, scipy, and statistical modeling techniques. Interest in time series analysis and algorithmic trading strategies. We are looking for passionate, eager learners who are excited about the project at hand. LinkedIn). All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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