# Quantitative Researcher at IMC Trading

> United States · Unspecified · Other · open. Source: https://alderhq.app/jobs/greenhouse%3Aimc%3A4987748101 (read 2026-11-05).

## Facts (observed)

- Company: [IMC Trading](https://alderhq.app/companies/imc-trading)
- Location text: Chicago, United States; New York, United States; Chicago; New York
- Where it can be done from (inferred): United States (evidence: "Location: Chicago, United States; New York, United States; Chicago; New York")
- Posted: 2026-10-30 (6 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/4987748101
- Skills listed (inferred): Python, PyTorch

## Pay and sponsorship

- Posted pay: $175k–$275k 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)

IMC Americas, Inc. has multiple openings for Quantitative Researcher (REQ ID: 4528527101) in Chicago, IL and New York, NY.

Your Core Responsibilities

- Collaborate with traders, developers, and researchers to evaluate, validate, and improve quantitative models used in IMC’s proprietary trading strategies through statistical analysis, simulation, and empirical research (10%).
- Design quantitative methods to gather and analyze market data, trading statistics, or new data sources and use the result of that research as the basis for new trading strategies (10%).
- Build research-oriented computational tools, simulations, visualizations, and backtesting frameworks to evaluate quantitative hypotheses and measure model performance before production deployment (10%).
- Formulate trading hypotheses as mathematical, statistical, and machine-learning models; prototype algorithms and coordinate with developers to integrate validated research into trading systems (10%).
- Apply statistical inference, optimization, numerical methods, and financial mathematics to diagnose model behavior, improve forecasting accuracy, and address complex research problems in proprietary trading (15%).
- Identify gaps in existing trading algorithms and propose new algorithmic approaches to improve pricing, execution, risk management, or trading performance (10%).
- Define design requirements for new quantitative trading algorithms, including the intended market behavior, data inputs, model assumptions, implementation constraints, and expected trading impact (10%).
- Drive complex quantitative research projects from initial problem definition through hypothesis testing, model validation, implementation planning, and post-deployment performance review (10%).
- Determine whether quantitative models or trading strategies are ready for production deployment by assessing statistical evidence, trading risk, operational constraints, and expected profitability (5%).
- Prioritize quantitative research initiatives by weighing expected PnL impact, technical feasibility, implementation risk, resource requirements, and strategic value to the trading desk (5%).
- Mentor graduate quantitative researchers and interns by reviewing research plans, challenging assumptions, evaluating analysis quality, and providing technical guidance on algorithm design, trading research, and model validation (5%).
Partial telecommuting permitted. Multiple positions available. Requisition ID: 4528527101.

Your Skills and Experience

This position requires a Bachelors degree, or foreign equivalent, in Computer Science, Financial Mathematics, Financial Engineering, Computational Mathematics, or a closely related quantitative, mathematical, or computational field, and two (2) years of experience in the job offered or a quantitative, technical, and mathematical role or a related position.

Must have two (2) years of experience with each of the following skills:

- Applying statistical inference, optimization, regression analysis, time-series analysis, algorithm design, and other analytical and quantitative techniques to solve complex problems;
- Designing and implementing mathematical models and algorithms, including optimization, signal-generation, and statistical learning methods;
- Analyzing large-scale, high-frequency financial time-series datasets — including market data, order book data, trade data, and derived quantitative signals — to identify patterns, evaluate hypotheses, and measure model performance, with experience handling data quality issues such as gaps and outliers;
- Applying statistical inference, time-series analysis, and model-validation best practices to analyze data and evaluate quantitative research results;
- Applying concepts from financial theory, financial mathematics, and financial engineering, including market microstructure, derivatives pricing, risk modeling, and portfolio management;
- Experience collaborating with traders and developers conducting quantitative research for use in a quantitative trading environment;
- Using Python coding libraries, including Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost, LightGBM, Numba, Polars, Dask, Matplotlib to assist in quantitative analysis;

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aimc%3A4987748101 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.