Job Description
About the Company
My client is a leading global investment management firm that delivers high-quality, uncorrelated returns through a diversified set of systematic and quantitative strategies across global financial markets. The firm’s success is driven by deep expertise in trading, technology, and operations, underpinned by rigorous scientific research. As a highly technology- and data-driven organization, it builds proprietary, cutting-edge systems ranging from high-performance trading platforms to large-scale data analytics and compute infrastructure. With a global footprint, the firm fosters true cross-border collaboration by aligning investment, technology, and operations teams worldwide. Complementing its systematic platform, the firm also runs discretionary strategies to capitalize on opportunities not well suited to purely systematic trading.
About the Role
Role/Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in equity markets.
Responsibilities
- End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
- Identify and evaluate new datasets for stock return predictions
- Maintain and improve the portfolio trading in the production environment
Qualifications
- MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
- Previous experience within top hedge funds or investment banks as a quantitative researcher
Required Skills
- Demonstrated proficiency in Python
- Strong command of foundations of applied statistics, linear algebra, and time series models
- Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources
- Knowledge of financial markets
- Highly motivated, willing to take ownership of his/her work
- Collaborative mindset with strong independent research ability
- Commitment to the highest ethical standards
Preferred Skills