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: Quantitative Science is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our scientists are in constant search of new algorithms and methodologies. Scientists at WorldQuant develop high-quality models that add value to our frameworks.
WorldQuant is seeking an outstanding individual to join our team as an AI Science Intern. The person must have a strong understanding of the scientific machine learning process to be able to work with established scientists to build computer-based models. While prior finance experience is not required, a successful candidate must also possess a strong curiosity about learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges.
- Work with the senior team members to develop and implement machine learning models, products, and workflows.
- Help test and generally improve the performance of existing models
- Onboard and explore behaviors of Large Language Models
- Port cutting edge python code running in Jupyter notebooks to internal frameworks
- Explore academic literature on advanced machine learning and mathematical concepts
- Document code, frameworks, and experiments
What You’ll Bring:
- Pursuing a PhD at an accredited four-year university in a quantitative field (e.g., Computer Science, Mathematics, Electrical Engineering, Physics)
- Strong programming skills in Python
- Experience designing, implementing and experimenting with ML models such as FFNNs, RNNs, CNNs, and Transformers
- Strong evidence of being a self-starter and problem-solver
- Research experience in NLP, Deep Learning, or AI is a plus
- Familiarity with platforms such as Linux is a plus
- Interest in financial markets
By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.
Copyright © 2024 WorldQuant, LLC. All Rights Reserved.
WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.