Quantitative Researcher New

Trading Interview

Chicago, New York (IL, NY)

Hybrid

USD 175,000 - 275,000

Full time

8 days ago

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Benefits offered by this job

Partial telecommuting allowed

Job summary

IMC Americas, Inc. is hiring Quantitative Researchers in Chicago, IL and New York, NY. You will validate models used in proprietary trading, design methods to analyze market data, and build backtesting frameworks for trading strategies.

You will prototype algorithms, apply financial math, and collaborate with traders and developers to enhance pricing, execution, and risk management. This role emphasizes low-latency trading insights and robust research practices.

Qualifications

  • Requires a Bachelor's degree in a quantitative field and two years of relevant experience.
  • Experience with statistical inference, regression, time-series analysis.
  • Experience with large-scale financial time-series data and data quality issues.
  • Collaborates with traders and developers in quantitative research.
  • Proficient in Python data libraries for quantitative analysis.

Responsibilities

  • Collaborate with traders, developers, and researchers to validate models used in trading strategies.
  • Design quantitative methods to analyze market data and trading statistics for new strategies.
  • Build tools, simulations, visualizations, and backtesting frameworks to test hypotheses.
  • Formulate trading hypotheses as mathematical models and prototype algorithms.
  • Apply financial mathematics to diagnose model behavior and improve forecasting accuracy.
  • Identify gaps in trading algorithms and propose new algorithmic approaches.
  • Define design requirements for new trading algorithms and their market impact.
  • Drive complex quantitative research projects from problem to deployment and review.
  • Assess readiness of models for production deployment considering risk and profitability.
  • Prioritize initiatives by potential PnL impact and feasibility, mentoring junior researchers.

Skills

Statistical inference
Time-series analysis
Algorithm design
Quantitative research
Financial mathematics
Model validation
Data analysis
Python programming
Low-latency concepts
Collaborating with traders

Education

Bachelor's degree in a quantitative field

Tools

Pandas
NumPy
SciPy
Scikit-learn
PyTorch
XGBoost
LightGBM
Numba
Polars
Dask
Matplotlib

Job description

Chicago, United States; New York, United States

Job Type Full-time

Job description

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 aBachelors 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.

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.

IMC is a global trading firm and liquidity provider, headquartered in Amsterdam. It started in 1989 with two traders working together on the floor of the Amsterdam Equity Options Exchange,…

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