Financial Services, Proprietary Trading, FinTech

Quantitative Researcher

RemoteRemoteFull Time$175,000–$275,000 /yrPosted 8 days agoVisa sponsorship available

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Required skills

quantitative models
statistical analysis
simulation
empirical research
quantitative methods
market data
trading statistics
trading strategies
computational tools
backtesting frameworks

Nice to have

partial telecommuting

Role summary

IMC Americas, Inc. seeks Quantitative Researchers in Chicago, IL and New York, NY to collaborate with traders and developers on quantitative models for proprietary trading strategies. Responsibilities include designing quantitative methods, analyzing market data, building research tools, formulating trading hypotheses, applying statistical inference and financial mathematics, identifying algorithmic improvements, defining algorithm requirements, and driving research projects from inception to post-deployment review. The role involves assessing model readiness for production, prioritizing research initiatives, and mentoring junior researchers. Requires a Bachelor's degree in a quantitative field and two years of experience in quantitative research, statistical analysis, financial mathematics, Python, and algorithmic trading.

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;

Applying quantitative research methodologies for use in quantitative proprietary trading;

Using numerical optimization techniques;

Building options portfolios; and

Developing trading systems that trade on low latency scale at the milisecond granularity.

#LI-DNI

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$175,000—$275,000 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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Quantitative Researcher

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