Quantitative Developer

As a member of the Quant Technology team at a prominent hedge fund, you will play a vital role in developing the next generation of in-house analytics and trading support tools. Your responsibilities will include creating and maintaining in-house models and pricing libraries to deliver real-time risk and Profit & Loss analysis for global trading activities in diverse financial products. Key Responsibilities: - Participate in the development and enhancement of the back-end distributed system to ensure continuous delivery of Risk and Profit & Loss information to Portfolio Managers and Risk Officers. - Collaborate closely with Quant researchers, developers, tech teams, middle office, and trading teams in London and New York / Miami. - Develop microservices on top of the new analytics library, integrating it into the existing system using the latest technologies. Qualifications Required: - Substantial experience in developing with Python, Go, or other object-oriented programming languages with a willingness to work with Python or Go. - Proficiency in Client-Server, Distributed computing, and Microservices design patterns. - Experience in developing and maintaining back-end distributed systems. - Good understanding of various Design Patterns, Algorithms & Data structures. - Familiarity with Git / GitHub. - Bachelor's degree in computer science or a quantitative field. - Effective communication skills with senior stakeholders. - Ability to work independently in a fast-paced environment with attention to detail and strong ownership of work. Desirable Skills And Qualifications: - Experience with Docker/Kubernetes. - Familiarity with NoSQL databases like MongoDB. - Experience with asynchronous programming in Python and the asyncio library. - Knowledge of reactive and/or functional programming. - Proficiency in a Linux environment. - Experience with Continuous Integration and Deployment (CI/CD). - Proficiency in Java or C++ with a good understanding of Modern C++ standards. - Experience in developing Cross Asset Pricing and Risk Systems. - Understanding of financial mathematics and statistics. - Previous experience in the financial industry.,