Quantitative Developer

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. Technologists at WorldQuant research, design, code, test and deploy projects while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We are looking for an exceptionally strong software engineer to join our Technology organization at WorldQuant. You will be part of a business-facing team responsible for building and evolving the core systems that power our Quant strategies. This is an AI-forward team: large language models (LLMs) and AI agents are part of our daily workflow — from writing and reviewing code, to automating operational toil, to building internal copilots and agentic tools that the whole team relies on. You won't just use AI to move faster; you'll help shape how it's applied across our engineering practice. Design and build data pipelines and the data layer. Develop and maintain the computational frameworks and infrastructure that run our quantitative strategies at scale. Implement and enhance quant-related software systems for data, research, portfolio construction, and trading. Work closely with Researchers, and Quants as a hands-on engineering partner, helping them turn ideas into robust production solutions. Gain exposure to the full lifecycle of the systematic/quant business, from data ingestion through research, implementation. Build and integrate AI-powered tooling - LLM agents, copilots, and automation - into engineering and research workflows. Use AI coding assistants and agentic developer tools to ship higher-quality software faster.