for Quotes). Use Generative AI to develop cutting-edge Trading Assistants Design and develop automated systems to perform pricing, market analysis, and risk management using Python, Java, SQL, KDB/Q, on Linux, Windows platforms, and distributed systems, for the Fixed Income Finance business. Design and implement a full-stack system with Python and JavaScript to provide a … quantitative models for the Fixed Income trading business, leveraging mathematical and computer science methods including mathematical finance, statistics, probability, and software engineering. Design database structures and write SQL and KDB queries for data manipulation and retrieval, including creating, updating, and optimizing database schemas, performing CRUD operations, and implementing stored procedures and functions to ensure efficient data processing and integrity. … in JavaScript and API in Python. A proven understanding of quantitative model validation, including model risk assessment, performance testing, and stability/stress testing. Skill in writing SQL and KDB/Q queries for customized data retrieval with performance optimization techniques. Proficiency in Python, C++, JavaScript, and the Q language in KDB+ database. What We Can Offer You: Strategic More ❯
A leading international bank is expanding its Fixed Income eTrading capability and seeking a talented Quant Developer to help design and deliver the next generation of electronic trading systems. This is a front-office, hands-on role working directly with More ❯
London | Hybrid | Permanent Ncounter is supporting a global technology-driven investment firm in hiring a Technology Integration Specialist to join a highly collaborative team that bridges development, infrastructure, and support. This function ensures trading systems and data services work seamlessly More ❯
The Kdb database, is widely used in the financial services industry, particularly by major investment banks, for high-speed, Real Time data processing and analytics. Kdb+ is a high-performance, column-based, in-memory database optimized for time-series data analysis, commonly used in financial services for handling large Real Time and historical datasets. It is developed and uses … performance language used for building data analytics solutions. Use cases: Widely adopted by major financial institutions for high-frequency trading, Real Time analytics, and historical data storage and retrieval. Kdb Insights Database: A more recent, distributed version of kdb+ designed for scalability with features like scalable query routing and temporal storage tiering. More ❯
