Curate, cleanse, validate, and maintain large US equity and options datasets; integrate fundamental and alternative data; build data pipelines for research and trading; perform statistical and ML analysis to identify market patterns; document data provenance and collaborate with engineers and traders to deploy production-grade models.
We are seeking a highly analytical and detail-oriented Quantitative Researcher to join our dynamic research team. The ideal candidate will have deep experience curating and analyzing a broad range of trading-related data sources-including traditional market data, fundamental datasets, and other vendor-supplied information. This role will contribute to the development of innovative trading strategies, support data-driven decision-making, and collaborate closely with trading, technology, and data acquisition teams.
Key Responsibilities:
Required Skills & Experience:
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Key Responsibilities:
- Curate, cleanse, and validate large volumes of market data, focusing on US equity and equity options
- Integrate, preprocess, and evaluate fundamental & alternative data sources
- Work closely with data acquisition & global data team to assess data quality
- Build and maintain robust data pipelines for research and live trading environments
- Perform data analysis ad statistical modeling to identify patterns and inefficiencies in the market
- Ensure the accuracy, completeness, and timeliness of datasets used in quantitative modeling.
- Document research processes, data provenance, and results with high standards of clarity and reproducibility
- Collaborate with software engineers and traders to translate research into production-grade models and tools
- Conduct quantitative research and analysis to support and enhance trading strategies
Required Skills & Experience:
- 3+ years of experience in a quantitative research or data-focused role in financial markets, ideally in a systematic trading environment
- Proven experience working with a diverse range of trading and financial data
- Must have previous knowledge of options markets and experience working with options data
- Hands-on experience integrating and analyzing non-market data sources is a plus
- Strong understanding of data vendor landscape
- Advanced proficiency in Python
- Experience with databases (SQL) and handling large datasets efficiently
- Familiarity with real-time data systems and tick-level data processing
- Familiarity with statistical and machine learning techniques
- Exceptional attention to detail and a systematic approach to problem-solving
- Strong written and verbal communication skills
#LI-DNP
Top Skills
Databases
Machine Learning
Python
Real-Time Data Systems
SQL
Tick-Level Data Processing
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