Deep Researcher

Other

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.

The Role:

WorldQuant is seeking an exceptional individual to join as Quantitative Researcher (Deep Research).

Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models.

As part of this role, you will:

Build predictive signals using a structured and methodical research process combining fundamental knowledge, data exploration and quantitative analysis
Become a domain expert on each fundamental topic you cover, identify key information drivers to target your research
Stay updated on the latest advancements in AI and LLM research, identifying opportunities to integrate them into quantitative finance applications

What You’ll Bring:

Bachelor's (Hons), Master's or PhD degree in in a highly quantitative or highly analytical field e.g. Math, Physics, Computer Science or Financial Engineering from a leading university with excellent academic records are strongly preferred
At least 2 years of relevant financial research experience
Creative problem solver with a passion for experimentation and tackling unsolved challenges
Strong foundation in mathematics, statistics, and quantitative modeling
Strong interest in financial markets
Proficiency in Python and C++
Knowledge and hands-on experience in AI, Machine Learning (ML), and LLMs is a plus
Excellent communications skills (both written and oral English)

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