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Data Science Sports Jobs in Chicago, IL (NOW HIRING)

Data Engineer

Chicago, IL · On-site

$100K - $115K/yr

A four-year degree in Computer Science, Data Science, Mathematics, Engineering, or a related field ... Strong interest in sports and sports analytics. * Familiarity with marketing data (e.g., campaign ...

Company Description Wolf Soccer Club is a growing sports organization dedicated to fostering ... Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a ...

Company Description Wolf Soccer Club is a growing sports organization dedicated to fostering ... Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a ...

Company Description Wolf Soccer Club is a growing sports organization dedicated to fostering ... Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a ...

Listings Specialist

Chicago, IL · On-site

$130K - $150K/yr

This role is designed for someone who codes well, thinks like a data scientist, and is genuinely curious about the events shaping sports, politics, and economics. What you'll do * Manage and evaluate ...

Listings Specialist

Chicago, IL · On-site

$130K - $150K/yr

This role is designed for someone who codes well, thinks like a data scientist, and is genuinely curious about the events shaping sports, politics, and economics. What you'll do * Manage and evaluate ...

Listings Specialist

Chicago, IL · On-site

$130K - $150K/yr

This role is designed for someone who codes well, thinks like a data scientist, and is genuinely curious about the events shaping sports, politics, and economics. What you'll do * Manage and evaluate ...

RSI) is a market leader in online casino and sports betting, currently operating real-money gaming ... Collaborate with Data Science and Marketing Analytics teams to create affiliate performance ...

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Showing results 1-20

Data Science Sports information

See Chicago, IL salary details

$23.1K

$109.3K

$209.4K

How much do data science sports jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data science sports in Chicago, IL is $109,329.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,268.00 and $158,068.00 per year, depending on experience, location, and employer.

What is a Data Science Sports?

A Data Science Sports job involves using data analytics, machine learning, and statistical models to extract insights from sports-related data. Professionals in this field analyze player performance, team strategies, injury prevention, and fan engagement to help teams, coaches, and organizations make data-driven decisions. They work with large datasets, build predictive models, and create visualizations to uncover trends and patterns. This role is essential in modern sports for optimizing performance, scouting talent, and enhancing the overall fan experience.

What does a Data Science Sports professional do?

In a Data Science Sports role, your daily tasks often involve extracting, cleaning, and analyzing large sets of sports-related data to uncover performance trends or predictive insights. You’ll likely collaborate closely with coaches, scouts, and other team members to translate your findings into strategic recommendations. Creating data visualizations, building predictive models, and presenting reports to non-technical stakeholders are also common parts of the job. This dynamic environment requires adaptability and a passion for both sports and data-driven problem solving.

What skills and qualifications are needed for a Data Science Sports position?

To thrive in Data Science Sports, you need strong analytical skills, statistical knowledge, and experience with sports data combined with a background in mathematics, statistics, or computer science. Familiarity with programming languages like Python or R, data visualization tools, machine learning platforms, and relevant sports analytics software is highly valuable. Effective communication, problem-solving abilities, and a collaborative mindset are crucial soft skills in this field. These competencies enable professionals to turn complex sports data into actionable insights that drive decision-making for teams, coaches, and organizations.

How much do data science sports make?

Data science roles in sports typically have salaries ranging from $60,000 to over $120,000 annually, depending on experience, location, and the level of responsibility. Professionals often use skills in statistics, machine learning, and data visualization tools to analyze athletic performance, team strategies, or fan engagement. Entry-level positions may start lower, while senior roles or those in major leagues tend to pay higher salaries.

What do data science sports do in sports?

Data science professionals in sports analyze large datasets to improve team performance, player health, and game strategies. They use statistical models, machine learning, and data visualization tools to identify patterns and inform decision-making in areas like player recruitment and game tactics.

What are the most commonly searched types of Data Science Sports jobs in Chicago, IL?

The most popular types of Data Science Sports jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Data Science Sports jobs?

Cities near Chicago, IL with the most Data Science Sports job openings:

Infographic showing various Data Science Sports job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $109,329 per year, or $52.6 per hour.

$100K - $115K/yr

Full-time

Re-posted 16 days ago


Job description

Position Summary: The Excel Analytics team is growing, and we are seeking a Data Engineer to help build and maintain the data pipelines and platforms that power our reporting, modeling, and client deliverables. This is a hands-on role for an early-career engineer who takes pride in building things the right way-with testing, data quality, and reliability built in from the start, not bolted on later. You will work alongside senior engineers and analysts to ingest, transform, and deliver trustworthy data across the business. This role will be based out of the Excel Chicago office.

Role & Responsibilities:

  • Build, maintain, and optimize data pipelines that reliably ingest, transform, and export data from internal and external sources.
  • Write and maintain automated tests-unit, integration, and data-quality checks-to ensure pipelines and datasets are correct, complete, and trustworthy.
  • Develop Python-based data workflows and orchestration tasks following established team patterns.
  • Contribute to relational data design-tables and relationships, primary/foreign keys, and appropriate indexing-and deliver schema changes as version-controlled migrations.
  • Support the data lake and warehouse layer (S3, Athena/Glue, PostgreSQL/Aurora), helping keep schemas, models, and documentation accurate.
  • Contribute to CI/CD pipelines and containerized (Docker) workflows, ensuring changes are tested and deployed safely.
  • Investigate and resolve data and pipeline issues, and help improve monitoring so problems are caught early.
  • Provide production support for data pipelines during standard working hours.
  • Collaborate with analysts, engineers, and client-facing teams to turn business needs into clean, documented solutions.

Education and Experience:

  • A four-year degree in Computer Science, Data Science, Mathematics, Engineering, or a related field OR equivalent experience.
  • 2+ years of professional experience in data engineering, software engineering, or a closely related role.

Required Qualifications:

  • Proficiency in Python and SQL, with hands-on experience building or maintaining data pipelines.
  • Demonstrated commitment to testing-writing unit and integration tests and validating data quality (e.g., pytest, schema/row-level checks, or similar).
  • Experience with OLTP (row-oriented) databases (PostgreSQL, MySQL, or equivalent).
  • Experience with OLAP (columnar) databases (Clickhouse, Redshift or equivalent).
  • Solid grasp of data modeling, indexing, and schema migrations.
  • Working knowledge of cloud environments (AWS preferred; GCP/Azure acceptable).
  • Familiarity with Git and CI/CD pipelines, and an understanding of data and software engineering best practices.
  • Exposure to AI/ML or Generative AI/LLM-driven solutions.
  • Awareness of data security, access controls, and observability/monitoring practices.
  • Ability to work collaboratively, take ownership of your work, and operate in a fast-paced environment.

Knowledge, Skills and Abilities:

  • Experience with Apache Airflow or other workflow orchestration tools.
  • Familiarity with Terraform or Infrastructure-as-Code.
  • Familiarity with event-driven or serverless architectures (e.g., S3/SQS-triggered pipelines, Lambda).
  • Experience building APIs or services to expose data (FastAPI, Flask, or similar).
  • Experience with BI tools (Power BI, Tableau).
  • Experience working in the sports industry and/or the agency world.
  • Strong interest in sports and sports analytics.
  • Familiarity with marketing data (e.g., campaign, audience, engagement, and brand/sponsorship metrics);

The pay range for this position is: $100,000 per year - $115,000 per year. This position is also eligible for benefits and discretionary bonus.

Ultimately, the salary may vary based upon, but not limited to, relevant experience, time in role, business sector, and geographic location, among other criteria.