As an AI Research Scientist, you will build mathematical models for investment evaluation, contribute code, and create analytical reports while collaborating with researchers and business leaders in quantitative finance.

Design and build real-time market data processing systems, providing technical leadership and innovating with emerging technologies for enhanced efficiency.

The Head of Reference Data leads the development of scalable reference data solutions, ensuring alignment with business goals and exceptional service for internal customers. Responsibilities include strategic leadership, architectural oversight, and driving Agile processes while mentoring engineering teams.

Lead the development of AI-driven solutions at WorldQuant by architecting scalable products, collaborating with teams, and mentoring junior engineers.

The Senior Technical Project Manager will lead project management activities, analyze data, build business relationships, and ensure effective project execution.

WorldQuant seeks candidates for its Technology team to join a community for potential future opportunities. The role highlights collaboration and innovative thinking.

Lead the maturation phase of crucial software systems, improving performance and scalability, while mentoring a team of developers.

Support Portfolio Managers with alpha research, modeling, and implementation of quantitative trading strategies while building tools for quantitative research.

Develop systematic strategies to exploit market inefficiencies, manage a quantitative investment portfolio, and build a research pipeline.

The Quantitative Developer will build AI and ML models for investment strategies, collaborating across departments to implement AI solutions.

Support Portfolio Managers with alpha research, modelling, and implementation of quantitative trading strategies while building tools for the quantitative research process.

Develop and manage systematic strategies for a diverse range of asset classes, utilizing quantitative management techniques to drive investment portfolios.

Develop and deploy systematic financial strategies through high-quality predictive signals using production-quality code primarily in C++ on a Linux platform. Collaborate with research teams to build scalable, distributed systems.