AI Scientist
About The Position
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: We are seeking an exceptionally talented AI Scientist to join the Artificial Intelligence team at WorldQuant. The successful candidate will conduct research in the Machine Learning field to improve multiple aspects of the investment pipeline, produce trading or predictive signals using innovative Machine Learning algorithms, apply the latest in LLM based agentic technology to develop and test innovative trading signals and algorithms, implement signal compression and combination techniques using Machine Learning tools, implement state of the art machine learning algorithms, design deep learning architectures, develop model frameworks for investment professionals, collaborate with portfolio managers and researchers to optimize machine learning algorithms, and communicate optimally with team members, researchers, and portfolio managers.
Requirements
- PhD degree in a quantitative or highly analytical field (e.g., Computer Science, Physics, Mathematics, Statistics, or a related field)
- 2+ years of research or work experience applying Machine Learning in innovative ways to complex problems
- Graduated at the top of your respective educational program, with excellent problem-solving abilities, insight, and judgment with a strong attention to detail
- Demonstrated ability to program. Strong development skills and proficiency in C++, Python, and PyTorch.
- Demonstrated science aptitude via record of creativity and inventions. Ability to run experiments and perform statistical inference.
- Experience with software development tools and practices, such as version control (e.g., Git), continuous integration, and testing frameworks
- Advanced practitioner-level knowledge of statistical inference, machine learning, software solvers, and/or mathematical optimization
- Strong communication skills; ability to express complex concepts in simple terms
Responsibilities
- Conduct research in the Machine Learning field to improve multiple aspects of the investment pipeline
- Produce trading or predictive signals using innovative Machine Learning algorithms
- Apply the latest in LLM based agentic technology to develop and test innovative trading signals and algorithms
- Implement signal compression and combination techniques using Machine Learning tools
- Implement state of the art machine learning algorithms
- Design deep learning architectures
- Develop model frameworks for investment professionals
- Collaborate with portfolio managers and researchers to optimize machine learning algorithms
- Communicate optimally with team members, researchers, and portfolio managers
Benefits
- Fully paid medical and dental insurance for employees and dependents
- Flexible spending account
- 401k
- Fully paid parental leave
- Generous PTO (paid time off) that consists of: twenty vacation days that are pro-rated based on the employee’s start date, at an accrual of 1.67 days per month, three personal days, and ten sick days.
- Employee discounts for gym memberships
- Wellness activities
- Healthy snacks
- Casual dress code
- Learning and development courses
- Speakers
- Team-building off-site
- Employee resource groups
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
