In this role you will help build and scale WorldQuant’s quantitative research and portfolio platform. You will work on high-performance, distributed software that powers large-scale research operations and live trading workflows. You’ll collaborate with researchers and portfolio managers to deliver a robust, scalable system for alphas and strategies. This is a multi-year effort to evolve the platform for the firm’s next decade of growth, in a culture that blends academic rigor with accountability.
Responsibilities
develop large-scale, distributed systems to support research and production use
implement and maintain Python production code on Linux platforms
contribute to backtesting platform design and development
collaborate with researchers and portfolio managers to translate requirements into robust software
optimize performance, concurrency, and data handling for high-throughput workloads
own components of the software platform and address technical challenges
stay motivated and work independently with minimal direction
Key requirements
minimum 7 years of production-quality Python on Linux
willingness to learn C++ (strong plus)
interest in machine learning, deep learning, backtesting, and platform development
strong Linux system programming fundamentals
ability to design and develop large-scale distributed systems
solid understanding of data structures, algorithms, high-performance design, and concurrency
self-motivated with ability to work independently
proficiency in English
experience with computation on large-scale graph data or streaming/dataflow systems is a plus
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