# Systematic Index Options Trader at IMC Trading

> United States · Unspecified · Other · open. Source: https://alderhq.app/jobs/greenhouse%3Aimc%3A4861099101 (read 2026-11-05).

## Facts (observed)

- Company: [IMC Trading](https://alderhq.app/companies/imc-trading)
- Location text: Chicago, United States; Chicago
- Where it can be done from (inferred): United States (evidence: "Location: Chicago, United States; Chicago")
- Posted: 2026-06-01 (157 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.eu.greenhouse.io/imc/jobs/4861099101
- Skills listed (inferred): Python

## Pay and sponsorship

- Posted pay: $250k–$250k per year (from the listing's pay field)
- Market band for similar posted roles (Chicago, n 457): p25 $66k, median $98k, p75 $150k
- Recognised sponsor (NL): registered as "IMC Trading B.V." (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants))

## Description (the employer's text)

We are looking for an Index Options Low-Latency Execution Quantitative Trader to join our team. IMC's Index Options desk is one of the leading electronic liquidity providers in index options markets. Our execution team is responsible for getting IMC into the trades we want to participate in, across a range of mechanisms. Our ultra-low latency infrastructure is best-in-class, and because IMC is highly collaborative between traders, quant researchers, and developers, the scope of this role spans deep trade analysis, execution system improvement, and early ownership of a defined part of the strategy.

### Your Core Responsibilities

- Drive revenue in low-latency index options trading by building upon and improving our electronic execution systems
- Deliver high-quality analysis using a variety of datasets, including options pricing, trades data, and exchange feed
- Dive into specific trade examples to understand the behavior of our systems and those of our competitors, identify anomalies, and quantify opportunities
- Use backtesting and analysis tools to predict the impact of changes to our execution systems and continuously improve our performance
- Work collaboratively with traders, quant researchers, and developers to bring ideas from inception to production
- Take early ownership of a defined area of the strategy, for example a certain exchange or execution type, and grow into setting multi-month improvement plans
### Your Skills and Experience

- 2+ years of experience in low-latency index options execution, including liquidity providing and taking
- Strong understanding of exchange microstructure and how automated trading systems interact with exchanges
- Entrepreneurial mindset with a competitive nature, strong ownership mentality, and a bias toward action
- Ability to perform efficient analysis on large datasets in Python
- Preference for relevant tertiary qualifications (graduate or post-graduate) in a quantitative field: mathematics, computer science, statistics, or similar, with strong academic results
- Strong communicator, able to collaborate effectively across trading, research, and development teams
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—$250,000 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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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aimc%3A4861099101 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.