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Data Science Sports Jobs in Seattle, WA (NOW HIRING)

Twitch

Data Scientist

Seattle, WA · On-site

... sports, cooking, and more. It is where thousands of communities come together for whatever, every ... OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in ...

Twitch

Data Scientist

Seattle, WA · On-site

$157K - $212K/yr

... sports, cooking, and more. It is where thousands of communities come together for whatever, every ... OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in ...

The Walt Disney Company

Sr Data Engineer

Seattle, WA · On-site

$148K - $199K/yr

Bachelor's degree in Computer science, Information Systems, Software, Electrical or Electronics ... PE - Sports, News & Entertainment, Enablement Primary Job Posting Category: Data Engineering ...

The Walt Disney Company

Sr Data Engineer

Seattle, WA · On-site

$148K - $199K/yr

Bachelor's degree in Computer science, Information Systems, Software, Electrical or Electronics ... PE - Sports, News & Entertainment, Enablement Primary Job Posting Category: Data Engineering ...

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All JobsData Science Sports JobsData Science Sports Jobs in Seattle, WA

Data Science Sports information

See Seattle, WA salary details

$24.4K

$115.3K

$220.8K

How much do data science sports jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data science sports in Seattle, WA is $115,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,951.00 and $166,676.00 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 Seattle, WA?

The most popular types of Data Science Sports jobs in Seattle, WA are:

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

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

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

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

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

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

Data Science Sports jobs near you
Infographic showing various Data Science Sports job openings in Seattle, WA as of August 2026, with employment types broken down into 6% Internship, 62% Full Time, and 32% Part Time. Highlights an 100% In-person job distribution, with an average salary of $115,282 per year, or $55.4 per hour.

Senior Full Stack Data Scientist

Garuda Ventures

Seattle, WA • On-site

$120 - $150/hr

Other

Posted 21 days ago

Job description

About Arkero

Arkero is an AI company building intelligent automation solutions for professional sports organizations, ticketing platforms, and live entertainment businesses. We were founded on the conviction that the passionate professionals running these institutions deserve tools that amplify their expertise, not slow them down.

Our AI works alongside sports professionals, automating repetitive workflows so teams can focus on strategy, creativity, and the decisions that drive real business impact. If you're excited about applying cutting-edge AI to one of the most data-rich industries in the world, we'd love to hear from you.

The Role

We are seeking a highly skilled and innovative Senior Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering, with a focus on developing end-to-end data-driven solutions. This role offers an exciting opportunity to leverage advanced analytics and cutting-edge technologies to drive impactful business outcomes. You'll work across the full data science lifecycle: from data acquisition and feature engineering to model development, dashboard delivery, and stakeholder communication.

Key Responsibilities
  • Design, develop, and deploy end-to-end AI and machine learning solutions — from data acquisition and feature engineering through model training, validation, and production deployment.
  • Build and maintain robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from varied and often messy sources, with a strong focus on data quality and reliability.
  • Leverage AI and advanced analytics techniques to develop innovative, scalable solutions that drive impactful business outcomes.
  • Optimize model and AI system performance through feature engineering, hyperparameter tuning, rigorous validation, and continuous monitoring — treating calibration and drift as ongoing operational concerns.
  • Build scalable, maintainable software to integrate AI and data science workflows with existing systems, enabling seamless data-driven decision-making across the organization.
  • Establish and maintain monitoring mechanisms to proactively detect model drift, data quality issues, and performance degradation — identifying root causes and validating fixes.
  • Work closely with engineers, software developers, and business stakeholders to translate ambiguous business questions into structured AI-driven analyses with explicit assumptions and clear, audience-appropriate communication.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
  • 7+ years of hands-on experience across the full data science stack — from raw data acquisition and feature engineering to model deployment and production monitoring.
  • Experience with Claude Code, Codex, or other AI coding agents in delivering high quality data science work.
  • Strong proficiency in Python and SQL, with a solid foundation in software engineering best practices including version control, maintainable code, and working effectively in a shared codebase.
  • Deep understanding of machine learning algorithms, statistical modeling, and model validation — with proven experience productionizing ML models including drift detection, calibration, and performance monitoring.
  • Demonstrated experience with generative AI and large language models, including prompt engineering, fine-tuning, or integrating AI APIs into production workflows.
  • Experience developing and deploying end-to-end data science solutions in cloud environments, with familiarity across the modern AI/ML tooling ecosystem.
  • Strong written and verbal communication skills — able to translate complex AI-driven findings into clear, actionable insights for both technical and non-technical audiences.
Preferred Qualifications
  • Experience on a small or startup team — comfortable wearing engineering, analyst, and PM hats in the same week.
  • Experience with sports and ticketing platforms and data ecosystems such as Ticketmaster, SeatGeek, or similar.
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