Quantitative Researcher
Quantitative Researcher developing cutting-edge ML and statistical models to identify predictive signals in global financial markets. Requires PhD in a STEM field, strong Python skills, and interest in ML/AI; no finance experience needed. Matched to Alpha Research, Data Science, or Strategy Research teams.
About the job
Responsibilities
- Designing and implementing state-of-the-art machine learning models for large-scale prediction problems
- Working with massive structured and alternative datasets to uncover meaningful signals
- Developing novel statistical methods and predictive features
- Reading, evaluating, and extending cutting-edge academic research
- Designing experiments, testing hypotheses, and validating ideas through simulation
- Collaborating with experienced researchers across disciplines to transform research into production-ready strategies
Your research has a direct impact - from idea generation to live trading.
Researchers are matched to one of the following teams based on strengths and interests:
- Alpha Research: Discover predictive signals by developing new features, exploring diverse datasets, and building machine learning models that forecast market behavior.
- Data Science: Identify, acquire, engineer, and analyze large and unconventional datasets while partnering closely with researchers to unlock new predictive insights.
- Strategy Research: Develop systematic trading strategies using modern statistical and machine learning techniques, validating ideas against real market data through rigorous experimentation.
Requirements
- PhD in Computer Science, Physics, Mathematics, Statistics, Engineering, Economics, or another STEM discipline
- Strong interest in machine learning, statistics, or artificial intelligence
- Excellent programming skills in Python
- Outstanding analytical and problem-solving abilities
- Ability to work independently while collaborating effectively with multidisciplinary teams
- Curiosity, creativity, and a passion for solving difficult problems
No prior finance experience is required.
Nice-to-Haves
- Background in computer science, physics, mathematics, engineering, economics, statistics, or another STEM discipline
Compensation and Benefits
- Base salary: $150,000 to $200,000 (determined based on educational background and professional experience)
- Competitive salary plus discretionary, performance-based bonus
- PPO Health, dental and vision insurance premiums fully covered for you and your dependents
- Pre-tax commuter benefits
- Weekly company meals
- Collaborative, casual, and friendly work environment
Skills
Machine Learning, Python, Statistics, Artificial Intelligence, Data Analysis, Predictive Modeling, Hypothesis Testing, Simulation, Feature Engineering, Large-Scale Datasets
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