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Entry Level Algorithmic Trading Quant Jobs in Chicago, IL

Executing algorithmic trading strategies in accordance with the trading desk's objectives ... Assisting quantitative traders in performing research for new trading strategies Requirements ...

Executing algorithmic trading strategies in accordance with the trading desk's objectives ... Assisting quantitative traders in performing research for new trading strategies Requirements ...

Executing algorithmic trading strategies in accordance with the trading desk's objectives ... Assisting quantitative traders in performing research for new trading strategies Requirements ...

... algorithmic trading strategies deployed on electronic trading venues around the world. During an intensive period of mentorship and training in trade floor operations, Quantitative Traders learn the ...

Quantitative Trader

Chicago, IL · On-site

$150K - $200K/yr

... algorithmic trading strategies deployed on electronic trading venues around the world. During an intensive period of mentorship and training in trade floor operations, Quantitative Traders learn the ...

What you'll do: • Design and optimize systematic options trading strategies using quantitative research and machine learning techniques • Build and refine algorithmic trading models from ideation ...

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Entry Level Algorithmic Trading Quant information

See Chicago, IL salary details

$54.1K

$122.8K

$202.4K

How much do entry level algorithmic trading quant jobs pay per year?

As of Aug 3, 2026, the average yearly pay for entry level algorithmic trading quant in Chicago, IL is $122,758.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,900.00 and $157,100.00 per year, depending on experience, location, and employer.

What are some common challenges faced by entry level algorithmic trading quants during their first year on the job?

Entry-level algorithmic trading quants often encounter challenges such as adapting to fast-paced environments where quick decision-making and consistent performance are essential. They may need to bridge the gap between academic theory and real-world market behavior, learning to develop, backtest, and refine trading strategies under time constraints. Collaborating with traders, developers, and risk managers is also crucial, requiring strong communication skills to ensure strategies are both technically sound and aligned with business goals. Additionally, staying current with evolving market data and technology platforms is a constant learning curve.

What does an entry level algorithmic trading quant do?

An Entry Level Algorithmic Trading Quant is responsible for developing, testing, and implementing mathematical models and computer algorithms to execute trades in financial markets automatically. They analyze large datasets to identify trading opportunities, optimize trading strategies, and manage risks. Typically, they work closely with senior quants, software engineers, and traders to ensure the performance and reliability of trading systems. Their role often includes coding, statistical analysis, and monitoring live trades to ensure algorithms function as intended.

What are the key skills and qualifications needed to thrive as an entry level algorithmic trading quant?

To thrive as an Entry Level Algorithmic Trading Quant, you need strong quantitative skills, programming proficiency (often in Python or C++), and at least a bachelor's degree in a technical field such as mathematics, computer science, or engineering. Familiarity with data analysis tools, financial modeling software, and version control systems like Git is typically required, and knowledge of financial markets or certifications like CFA can be beneficial. Analytical thinking, attention to detail, and effective teamwork are crucial soft skills that set high performers apart. These competencies enable quants to develop robust trading strategies, identify market opportunities, and collaborate efficiently in a high-stakes, fast-paced environment.

What is the difference between Entry Level Algorithmic Trading Quant vs Quantitative Research Analyst?

AspectEntry Level Algorithmic Trading QuantQuantitative Research Analyst
Required CredentialsBachelor's in Math, CS, or Finance; programming skillsBachelor's or Master's in Math, Stats, or Finance; programming skills
Work EnvironmentTrading firms, hedge funds, financial institutionsResearch labs, financial firms, asset managers
Employer & Industry UsageHigh-frequency trading, algorithmic trading teamsResearch-focused, model development for investments
Comparison Search IntentYesYes

Entry Level Algorithmic Trading Quants focus on developing trading algorithms used in live markets, often working directly with trading desks. Quantitative Research Analysts primarily conduct research to develop models and strategies that inform investment decisions. While both roles require strong quantitative skills and programming knowledge, the Trading Quant emphasizes implementation in trading environments, whereas the Research Analyst emphasizes model development and analysis.

What are the most commonly searched types of Algorithmic Trading Quant jobs in Chicago, IL? The most popular types of Algorithmic Trading Quant jobs in Chicago, IL are:
What are popular job titles related to Entry Level Algorithmic Trading Quant jobs in Chicago, IL? For Entry Level Algorithmic Trading Quant jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Entry Level Algorithmic Trading Quant jobs in Chicago, IL look for? The top searched job categories for Entry Level Algorithmic Trading Quant jobs in Chicago, IL are:
Infographic showing various Entry Level Algorithmic Trading Quant job openings in Chicago, IL as of July 2026, with employment types broken down into 20% Locum Tenens, 14% As Needed, 44% Full Time, 7% Part Time, 1% Contract, and 14% Nights. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $122,758 per year, or $59 per hour.

Quantitative Trading Internship - 2027

Dime Line Trading

Chicago, IL

Internship

Posted 11 days ago


Job description

The internship at Dime Line is a 10-week opportunity with our team of quants, data scientists and traders, available all seasons of the year.

Dime Line Trading develops algorithms to trade all major US sports. Dime Line was founded in 2020 by veterans of the financial trading and sports betting industries, who started their careers in the sports gambling space before entering the financial industry, where they individually built successful trading teams at leading firms.

WHAT YOU'LL DO:
You will have the opportunity to work with our team while receiving feedback and mentorship from our tight-knit, collaborative employees in various roles. This is an opportunity to get your feet wet within the trading industry while utilizing algorithmic, statistical, and engineering concepts applied toward the sports betting industry. There are a number of different types of opportunities within Dime Line spanning quantitative research, algorithmic trading models, live trading, and data science. Interns will have the opportunity to work within multiple fields across multiple sports. We retain a startup culture, which means that interns will be working on production projects alongside the rest of the team.

SKILLS YOU'LL NEED:
Ability to work in a fast-paced environment and handle multiple demands at once
Interest in building solutions, solving problems, and understanding how things work
Interest in sports, sports analytics / sabermetrics - please let us know about your interest or work in sports analytics!

Hands-on experience and a high level of proficiency in one or more of the following:
- Statistical modeling, especially predictive modeling in Python/R
- Python development on Linux platform
- Building algorithmic trading models in financial markets, prediction markets or similar
- Quantitative sports gambling or daily fantasy sports

It's great to see:
- Past internship or job experience in a trading, quantitative or engineering role
- Advanced coursework in statistics, optimization, operations research, and computer science