1

Quantitative Modeling Jobs in Chicago, IL (NOW HIRING)

... in a quantitative field, and three or more years of relevant experience OR - MA/MS in a ... modeling techniques and validation methodologies • Strong programming skills in SAS, Python, SQL ...

... in a quantitative field, and three or more years of relevant experience OR - MA/MS in a ... statistical modeling techniques and validation methodologies Strong programming skills in SAS ...

Quantitative Modeler Manager - AML

Chicago, IL

$56.50 - $73.25/hr

Defending modeling approaches/methodologies/design decisions to both internal and external ... Basic Qualificati ons - Bachelor's degree in a quantitative field, and 10 or more years of relevant ...

Develop quantitative models describing market behavior. * Advance existing initiatives and explore opportunities for new research topics. Qualities that make great candidates: * Bachelors, masters ...

Sr. Quantitative Finance Manager

Chicago, IL · On-site

$112K - $153K/yr

Directs a quantitative team with model coverage of specified focus areas and oversees stakeholder engagement, including team effort in preparation for audit and regulatory exams * Sets quantitative ...

Sr. Quantitative Finance Manager

Chicago, IL · On-site

$112K - $153K/yr

Directs a quantitative team with model coverage of specified focus areas and oversees stakeholder engagement, including team effort in preparation for audit and regulatory exams * Sets quantitative ...

Showing results 41-60

Quantitative Modeling information

See Chicago, IL salary details

$101K

$175K

$267.5K

How much do quantitative modeling jobs pay per year?

As of Sep 5, 2026, the average yearly pay for quantitative modeling in Chicago, IL is $174,983.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,700.00 and $205,200.00 per year, depending on experience, location, and employer.

What is a quantitative modeling?

A Quantitative Modeling job involves using mathematical, statistical, and computational techniques to analyze data and construct models that help businesses make informed decisions. Professionals in this field work in finance, risk management, economics, and other industries to develop predictive models, optimize strategies, and assess uncertainties. They often use programming languages like Python, R, or MATLAB, along with machine learning and statistical methods, to solve complex problems.

What are typical daily tasks and projects for someone in a quantitative modeling role?

In a Quantitative Modeling position, your daily activities usually include analyzing large datasets, building and validating predictive models, and developing algorithms to solve business or financial problems. You might spend time coding, running simulations, and interpreting model outputs to inform strategy or risk assessment. Collaboration is common—you'll often work with data scientists, business analysts, or subject matter experts to refine models and ensure they're aligned with organizational goals. The work is intellectually stimulating and fast-paced, with opportunities to see your analytical insights directly impact decision-making.

What are the key skills and qualifications needed to thrive in the quantitative modeling position, and why are they important?

To excel in Quantitative Modeling, a strong foundation in mathematics, statistics, and data analysis is essential, often complemented by a degree in a quantitative field such as mathematics, finance, engineering, or physics. Proficiency in programming languages like Python, R, MATLAB, or statistical software, as well as familiarity with data visualization tools and financial modeling certifications (such as CFA or FRM), is highly valued. Effective quantitative modelers possess strong problem-solving abilities, attention to detail, and the ability to communicate complex findings clearly to both technical and non-technical stakeholders. These skills enable accurate, data-driven decision-making and the creation of robust predictive models in business, finance, or technology sectors.

What does a quantitative modeler do?

A quantitative modeler develops mathematical and statistical models to analyze financial data, assess risk, and support decision-making. They use programming languages like Python or R and tools such as Excel or specialized software, often working in finance, investment, or risk management environments.

What are the most commonly searched types of Quantitative Modeling jobs in Chicago, IL?

The most popular types of Quantitative Modeling jobs in Chicago, IL are:

What job categories do people searching Quantitative Modeling jobs in Chicago, IL look for?

The top searched job categories for Quantitative Modeling jobs in Chicago, IL are:

Infographic showing various Quantitative Modeling job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 49% In-person, and 51% Hybrid job distribution, with an average salary of $174,983 per year, or $84.1 per hour.

Quantitative Trading Strategist - Equity Options

IMC

Chicago, IL • On-site

$250K/yr

Full-time

PTO

Re-posted 10 days ago


Job description

IMC is seeking experienced quantitative professionals to join our US Equity Options market-making business. We are a leading scaled liquidity provider in US equity options, operating a large-scale systematic trading platform spanning thousands of underlyings. Our platform integrates quantitative research, trading strategy development, and production engineering within a collaborative, non-siloed environment across trading, research, and development teams.
This role focuses on improving how automated trading decisions are designed, evaluated, and deployed in live markets. You will work at the intersection of quantitative research, execution, and risk management to enhance pricing quality, execution performance, and overall system robustness. Improvements influence the broader platform rather than a single seat, providing meaningful ownership and impact from day one. Compensation is competitive and aligned with individual contribution.
Your Core Responsibilities:
  • Develop and refine quantitative models that improve pricing, execution, and risk management.
  • Analyze large-scale market and trading datasets to identify structural improvements.
  • Design, test, and deploy strategy enhancements into production systems.
  • Collaborate closely with traders, researchers, and engineers to iterate on live trading logic.
  • Contribute to scalable solutions that impact a broad universe of equity options products.
  • Drive research from idea generation through backtesting, implementation, and real-time monitoring.

Your Skills and Experience:
  • 3+ years of experience in quantitative research, systematic trading, or market microstructure-focused roles.
  • Experience working with exchange-traded products, ideally equity options.
  • Strong understanding of market structure and trading system behavior.
  • Demonstrated ability to conduct rigorous analysis on large, real-world datasets.
  • Strong programming skills (Python required; C++ or similar preferred).
  • Experience integrating research into production trading systems.
  • Background in statistics, probability, time series analysis, or optimization is strongly preferred.

The Base Salary 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
$250,000
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.