The individual in this role will be a part of our Core Development team which is responsible for designing, developing and maintaining our proprietary quantitative trading and research framework at Kronos. They will be focused on C++ functionality, alongside our Quant/Traders who will also be hands on with C++. You will be responsible for creating and optimizing scalable, multi-tiered applications and infrastructure. We are looking for someone who will be able to solve difficult technical problems in a fast-paced and energetic environment.
1. Responsible for developing and improving scalable quantitative research frameworks using Python, C++, and other software systems.
2. Designing and implementing a high-frequency trading platform, which includes collecting quotes and trades from and disseminating orders to exchanges around the world
3. Optimizing this platform by using network and systems programming, as well as other advanced techniques to minimize latency
4. Providing robust access to live and historical market data by leading development sprints and release cycles
5. Contributing towards the firm’s technical direction by driving new initiatives
Must have 1. A bachelor's or master’s degree in computer science or a related field 2. Expert background in data structures, algorithms, and OOP in C++ and strong Python/Bash; working knowledge of Linux 3. Strong understanding of computer systems e.g. operating systems, networks, performance optimization, etc 4. Experience in creating/supporting cross-platform multi threaded applications 5. Excellent problem solving skills and the ability to manage multiple tasks in a fast-paced environment 6. Passionate about designing in-house real-time systems that are robust, resilient, and extremely fast 7. A true self-starter, motivated to learn existing operations and uncover hidden problems 8. Strong communication skills and intermediate English speaking is required Nice to have 1. Experience in developing low latency systems 2. Experience in statistics/machine learning/grid-based computing