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Internship Predictive Modeling Jobs in Illinois (NOW HIRING)

Actuarial or related internship experience at an insurance carrier, broker, or consultancy ... Experience with statistical modeling and predictive analytics * Ability to work with large datasets ...

Actuarial or related internship experience at an insurance carrier, broker, or consultancy ... Experience with statistical modeling and predictive analytics * Ability to work with large datasets ...

Write customized programs in Python for meaningful data analysis and predictive modeling, and query ... Solid programming skills for data analysis - demonstrated through work, internships, coursework, or ...

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Internship Predictive Modeling information

What is the difference between Internship Predictive Modeling vs Data Analyst?

AspectInternship Predictive ModelingData Analyst
Required CredentialsTypically pursuing or recent graduate in data science, statistics, or related fieldsOften holds a degree in statistics, mathematics, or related disciplines
Work EnvironmentInternship setting, often in tech, finance, or marketing companiesFull-time or part-time roles in various industries including finance, healthcare, and retail
Employer & Industry UsageUsed in companies focusing on developing predictive models and machine learning applicationsCommon in organizations analyzing data trends, reporting, and decision-making

Internship Predictive Modeling focuses on developing and applying models to forecast outcomes, often as part of an internship program. Data Analysts interpret data, generate reports, and support business decisions. While both roles require analytical skills, predictive modeling emphasizes machine learning and statistical modeling, whereas data analysis centers on data interpretation and visualization.

What are the most commonly searched types of Predictive Modeling jobs in Illinois? The most popular types of Predictive Modeling jobs in Illinois are:

Quantitative Trading Internship - 2027

Dime Line Trading

Chicago, IL

Internship

Posted 8 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