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Salary
$250k – $300k per year
Location
In office (Chicago)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Aug 22, 2025. IMC Trading scores B on the Alion truth index.

Overview
Company
Impact
Profile match
IMC Trading is a proprietary trading firm and market maker headquartered in Amsterdam that trades its own capital, providing liquidity across more than 120 trading venues with in-house trading systems, low-latency infrastructure and machine learning models. Founded in 1989 by two traders on the floor of the Amsterdam equity options exchange, it now employs over 2,000 people of more than 70 nationalities in ten offices, including Chicago, New York, London, Zug, Sydney, Mumbai, Seoul and Hong Kong. It recruits quantitative researchers and traders, software, Python and systems engineers, machine learning researchers, and graduates and interns for its campus programmes.

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

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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