WorldQuant seeks to produce high-quality predictive signals (alphas) through its proprietary research platform to employ financial strategies focused on market inefficiencies.
Requirements
- Knowledge of global equity markets and their microstructure.
- Demonstrated ability to work on quantitative research projects: independently and as part of the team.
- Strong knowledge of Mathematics, Statistics, Optimization.
- Programming skills: Must possess at least 4 years of work with vector-based and relational databases (KDB+/Q or Vertica)
- Must have at least 4 years of experience with at least two of the following statistical packages: Matlab, R, Python
- Minimum of 4 years of experience in Investment Banking (Trading Division), Proprietary Trading, or Investment Management (Execution)
Responsibilities
- Providing recommendations to improving equity trading algorithms’ performance and reducing execution costs.
- Analyzing high frequency market and execution data for the purpose of extracting signals with price forecasting power.
- Developing and maintaining quantitative models and software solutions to measure and/or forecast price impact of trading and equity market properties.
- Creating statistical dark pool and exchanges ranking models.
- Developing methodology to compare brokers’ algo trading performance.
- Providing recommendations to distribution of funds among portfolio managers.
- Creating internal reports on trading PnL and trading algorithms’ performance.
Other
- Minimum of 4 years of experience in Investment Banking (Trading Division), Proprietary Trading, or Investment Management (Execution)
- Fully paid medical and dental insurance for employees and dependents, flexible spending account, 401k, fully paid parental leave, generous PTO (paid time off)
- Employee discounts for gym memberships, wellness activities, healthy snacks, casual dress code
- Learning and development courses, speakers, team-building off-site
- Base salary, discretionary performance bonus, and benefits
