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Sports Analytics Machine Learning Jobs in Geneva, IL

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

QF Analytics LLC is a fintech company that develops and supports one of the world's fastest-growing ... The Machine Learning Researcher should be interested in Financial Markets, and will be directly ...

Machine Learning Tutor

Dekalb, IL · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Machine Learning Tutor

Wheaton, IL · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Machine Learning Tutor

Chicago, IL · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Machine Learning Tutor

Schaumburg, IL · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Machine Learning Tutor

Naperville, IL · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

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Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do sports analytics machine learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a sports analytics machine learning specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.

What cities near Geneva, IL are hiring for Sports Analytics Machine Learning jobs?

Cities near Geneva, IL with the most Sports Analytics Machine Learning job openings:

Infographic showing various Sports Analytics Machine Learning job openings in Geneva, IL as of June 2026, with employment types broken down into 100% Full Time. Highlights an 84% In-person, and 16% Remote job distribution.

Quantitative Developer Internship - 2027

Dime Line Trading

Chicago, IL

Internship

Posted 26 days ago


Job description

This is a 10 week internship available all seasons of the year.
What you'll do:
  • Contribute to the research, design, and implementation of predictive statistical and machine learning models across prediction markets and exchange venues
  • Prototype and backtest models, monitor performance, and assist with optimizations.
  • Contribute to key feature development for model efficiency
  • Develop and maintain Python codebases in a Linux environment.
  • Help to design and implement new pricing models and frameworks
  • Support data pipeline and SQL database interactions for real-time models.
  • Assist in improving trading systems and operational tools.
  • Gain exposure to multiple sports, quantitative disciplines, and production engineering.
  • Other duties as assigned.

Skills you'll need:
  • Proficiency in Python (experience in R or other languages a plus).
  • Strong interest in statistical modeling, machine learning, or predictive analytics.
  • Familiarity with Linux and SQL databases.
  • Ability to work in a fast-paced environment and manage multiple tasks.
  • Interest in sports and sports analytics / sabermetrics.
  • Strong problem-solving and communication skills.
  • Predictable and reliable availability

It's great to see:
  • Coursework in statistics, optimization, computer science, or related fields.
  • Prior internship or project experience in trading, quantitative research, or software engineering.
  • Exposure to object-oriented development, real-time systems, or algorithmic trading models.
  • Experience with sports gambling, fantasy sports, or predictive analytics applied to sports.