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IMC Trading

Quantitative Researcher - Data Curation

IMC Trading, Chicago, Illinois, United States, 60290

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This range is provided by IMC Trading. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range $200,000.00/yr - $275,000.00/yr

Additional compensation types Annual Bonus

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

Curate, cleanse, and validate large volumes of market data, focusing on US equity and equity option

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 environment

Perform data analysis and 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

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

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Research and Finance

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