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Sports Data Science Internship Jobs in Seattle, WA

Conversica, Inc

Data Scientist

Seattle, WA · On-site

... for data science interns in the areas of natural language processing, natural language generation, and deep learning. Recognized by Gartner, INC, Harvard Business Review, etc, we are passionate ...

AEG

Intern, Data Science

Seattle, WA · On-site

$23/hr

Manager, Data Science Status: Hourly, Non-exempt Timeline: Preference will be given to candidates ... other sports research preferred. • Experience building and interpreting predictive models ...

New

Docugami

Data Science PhD Intern

Kirkland, WA

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking ...

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking ...

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All JobsSports Data Science JobsSports Data Science Internship JobsSports Data Science Internship Jobs in Seattle, WA

Sports Data Science Internship information

See Seattle, WA salary details

$13

$25

$47

How much do sports data science internship jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for sports data science internship in Seattle, WA is $25.61, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $27.88 per hour, depending on experience, location, and employer.

What is a sports data science internship?

A Sports Data Science Internship is a temporary position that allows students or recent graduates to gain hands-on experience applying data science techniques to sports-related problems. Interns typically work with data from games, athletes, or teams to analyze performance, develop predictive models, and support decision-making in sports organizations. This role often involves using programming languages like Python or R, working with large datasets, and collaborating with coaches or analysts. Interns may also assist in visualizing data and presenting insights to help improve team strategies or player development.

What types of projects or tasks can I expect to work on during a sports data science internship?

As a Sports Data Science Intern, you can expect to work on projects such as analyzing player performance data, building predictive models for game outcomes, and cleaning large datasets for use in analytics. Interns often collaborate with data scientists, coaches, and performance analysts to translate raw data into actionable insights. You'll likely use programming languages like Python or R and get exposure to sports-specific analytics software, providing valuable hands-on experience that can help launch your career in sports analytics.

What are the key skills and qualifications needed to thrive as a sports data science intern, and why are they important?

To thrive as a Sports Data Science Intern, strong quantitative skills, a background in statistics or data science, and experience with sports analytics are generally required. Familiarity with programming languages such as Python or R, data visualization tools, and knowledge of sports data platforms or databases is typical. Strong problem-solving abilities, attention to detail, and effective communication help interns stand out in team settings. These skills are crucial for analyzing complex sports data, generating actionable insights, and effectively conveying findings to coaches and decision-makers.

What is the difference between Sports Data Science Internship vs Sports Data Analyst?

AspectSports Data Science InternshipSports Data Analyst
Required CredentialsRelevant coursework, basic programming skillsDegree in statistics, data science, or related field
Work EnvironmentInternship programs, sports teams, analytics companiesFull-time roles in sports organizations, analytics firms
Employer & Industry UsageEntry-level, training-focused positions in sports analyticsProfessional, ongoing data analysis roles in sports

The Sports Data Science Internship is an entry-level, training-focused position designed for students or recent graduates gaining experience in sports analytics. In contrast, a Sports Data Analyst is a full-time professional role requiring more experience and specialized skills. Internships provide foundational exposure, while analysts handle ongoing data projects in sports organizations.

What are popular job titles related to Sports Data Science Internship jobs in Seattle, WA?

For Sports Data Science Internship jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Sports Data Science Internship jobs in Seattle, WA look for?

The top searched job categories for Sports Data Science Internship jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Sports Data Science Internship jobs?

Cities near Seattle, WA with the most Sports Data Science Internship job openings:

Sports Data Science Internship jobs near you
Infographic showing various Sports Data Science Internship job openings in Seattle, WA as of August 2026, with employment types broken down into 27% Internship, 38% Full Time, and 35% Part Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $53,270 per year, or $25.6 per hour.

Data Scientist

Seattle, WA • On-site

Conversica, Inc
Software Development • 51 - 200 employees
Learn more about Conversica, Incexternal

Full-time

Re-posted 10 days ago

Job description

One of the most commercially successful conversational AI companies in the world, Conversica is building the next generation of our artificial intelligence platform and we are looking for data science interns in the areas of natural language processing, natural language generation, and deep learning. Recognized by Gartner, INC, Harvard Business Review, etc, we are passionate, driven, self-starting, resourceful, innovative, collaborative, and we get a lot done while having fun. If that sounds like you, then read on!
Conversica is seeking talented and passionate data scientists to help us evolve our artificial intelligence, machine learning and natural language processing systems and technologies.
YOUR RESPONSIBILITIES
As Conversica's Data Scientist, you will work with other data scientists and engineers to solve and contribute to the innovative products we are building. You will be responsible for developing, improving and experimenting with methodologies and algorithms to support these efforts, using machine learning, deep learning, artificial intelligence and natural language processing techniques. Your scope will reach from text classification problems over big data analytics to A/B testing and experiment design.
JOB REQUIREMENTS
  • Experience and training in cutting-edge research in machine learning, natural language processing (NLP), text mining and computational linguistics.
  • Demonstrated success in using or (and preferably) developing machine learning models and data platforms in a production environment.
  • Training in deep learning approaches and natural language processing
  • Advanced proficiency with Python for data analysis
  • Must be fluent in either keras or tensorflow
  • Experience with large data sets (10 million+ rows)
  • Ability to convey rigorous mathematical concepts and considerations to non-experts
  • Experience working in an agile methodology

EDUCATION
Degree in a quantitative discipline such as Predictive Analytics, Statistics, Mathematics, or Computer Science with coursework in Machine Learning, Deep Learning, and Natural Language Processing; Masters/PhD preferred. Ideally we would like to see someone that has been published in Natural Language Processing and Deep Neural Networks.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Skills & Requirements Qualifications

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