Data Scientist

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Skills you'll use

What you'll do

• Research and engineer features from raw, high-frequency market data, translating market behavior hypotheses into quantitative signals.
• Implement signals within our internal simulation/backtesting framework, iterating between exploratory data analysis and framework-based implementation.
• Validate features through backtesting across historical data, checking behavior across different markets, regimes, and edge cases (e.g., market open/close, low-liquidity periods).
• Collaborate with research and engineering teams to align on implementation approaches, validation standards, and research decisions.
• Explore new and existing data sources to identify candidate signals worth developing further.
• Becoming a domain expert on different deep learning and machine learning applications for high frequency data, analyzing & understanding the underlying dynamics, market microstructure and behaviors within the data.
• Develop insights based on the data and collaborate with the research team to generate tradable
• Developing the utility tools that can further automate the software development, testing and deployment workflow.

About WorldQuant

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