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Quantitative Researcher - Data Curation

IMC Trading · Chicago, IL

Posted Sep 30, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a data error you caught that others missed. How did you find it?

What they are checking: Attention to detail, which the posting names as essential for this role.

Tell me about research you did that used curated data to find a market pattern.

What they are checking: Whether they can move from cleaning data to finding insight, which the role also requires.

What would you do

A vendor sends an alternative dataset and claims it predicts returns. How do you evaluate it?

What they are checking: Whether they check for survivorship, lookahead and real predictive value before recommending a buy.

A trader says a dataset looks wrong this morning, and trading starts soon. What do you do?

What they are checking: How they prioritize timeliness and accuracy under pressure without guessing.

How do you work with a data acquisition team when a vendor keeps sending late or incomplete files?

What they are checking: Collaboration across teams to fix data quality at the source.

About the work

How would you validate a day of US equity options market data before researchers use it?

What they are checking: Practical knowledge of the checks that catch bad quotes, gaps and timestamp problems.

How do you adjust historical equity data for splits, dividends and symbol changes?

What they are checking: Core data curation knowledge that quietly breaks research when done wrong.

How do you handle point-in-time issues with fundamental data so research doesn't use information that wasn't known yet?

What they are checking: Understanding of point-in-time data, a key source of false results in backtests.

How would you design a pipeline that serves the same data to both research and live trading?

What they are checking: Whether they can build robust pipelines that keep research and production consistent.

How do you document data provenance so someone can reproduce your results a year from now?

What they are checking: Their standards for documentation and reproducibility, which the posting stresses.

What statistical methods do you use to find outliers in market data without removing real events?

What they are checking: Judgment about cleaning data while keeping the real market behavior that matters.

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The full job description

As published by IMC Trading.

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. Your Core 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   Your Skills and 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 The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information. Salary Range $250,000 — $300,000 USD About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.  

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