IMC Trading Jobs

Quantitative Researcher

IMC Trading

Quantitative Researcher

Posted 9 Hours Ago

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2 Locations

Hybrid

Junior

Fintech • Machine Learning • Software • Financial Services

IMC is a proprietary trading firm powered by research and technology.

The Role

Conduct quantitative research for proprietary trading strategies by analyzing high-frequency market data, developing statistical and machine-learning models, building simulations and backtesting tools, and evaluating model performance. Collaborate with traders and developers to validate algorithms, improve pricing and execution, assess production readiness, prioritize research initiatives, and integrate validated models into low-latency trading systems. Mentor graduate researchers and interns.

Summary Generated by Built In

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

Skills Required

Bachelor's degree or foreign equivalent in Computer Science, Financial Mathematics, Financial Engineering, Computational Mathematics, or a closely related quantitative, mathematical, or computational field
Two years of experience in the job offered, or in a quantitative, technical, mathematical, or related role
Two years of experience applying statistical inference, optimization, regression analysis, time-series analysis, algorithm design, and quantitative techniques
Two years of experience designing and implementing mathematical models and algorithms, including optimization, signal generation, and statistical learning
Two years of experience analyzing large-scale, high-frequency financial time-series datasets, including market, order book, trade, and derived signal data
Two years of experience handling financial data quality issues such as gaps and outliers
Two years of experience applying statistical inference, time-series analysis, and model-validation practices
Two years of experience applying financial theory, financial mathematics, and financial engineering concepts, including market microstructure, derivatives pricing, risk modeling, and portfolio management
Two years of experience collaborating with traders and developers in a quantitative trading environment
Two years of experience using Python libraries including Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost, LightGBM, Numba, Polars, Dask, and Matplotlib
Two years of experience applying quantitative research methodologies for proprietary trading
Two years of experience using numerical optimization techniques
Two years of experience building options portfolios
Two years of experience developing trading systems operating at millisecond-level latency

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The Company

HQ: Amsterdam

1,954 Employees

Year Founded: 1989

What We Do

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 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.

Why Work With Us

At IMC, the best ideas win, regardless of hierarchy. Graduates receive mentorship and make an impact from day one, while experienced hires get to shape their own path in a flexible, high-performance environment. We remove barriers so everyone can grow and help drive one of the world’s leading liquidity providers.