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Sports Analytics Jobs in Seattle, WA (NOW HIRING)

The Seattle Times

Sports Multiplatform Editor

Seattle, WA · On-site

$63K - $95K/yr

Monitoring trends and readership analytics in real-time and providing the sports department with relevant information on SEO, trending topics and follow-up stories based on trending/breaking news.

Baden Sports Inc

Marketing Manager

Kent, WA · On-site

$85K - $110K/yr

Proficiency using AI-powered tools to enhance productivity, creative development, content generation, analytics, and overall marketing effectiveness. * Passion for sports and understanding of athlete ...

Baden Sports Inc.

Marketing Manager

Kent, WA · On-site

$85K - $110K/yr

Proficiency using AI-powered tools to enhance productivity, creative development, content generation, analytics, and overall marketing effectiveness. * Passion for sports and understanding of athlete ...

Baden Sports Inc

Marketing Manager

Kent, WA · On-site

$85K - $110K/yr

Proficiency using AI-powered tools to enhance productivity, creative development, content generation, analytics, and overall marketing effectiveness. * Passion for sports and understanding of athlete ...

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All JobsSports Analytics JobsSports Analytics Jobs in Seattle, WA

Sports Analytics information

See Seattle, WA salary details

$73.4K

$142.6K

$203.7K

How much do sports analytics jobs pay per year?

As of Sep 1, 2026, the average yearly pay for sports analytics in Seattle, WA is $142,625.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,800.00 and $169,600.00 per year, depending on experience, location, and employer.

What is sports analytics?

Sports analytics is a field of applied statistics that uses past performance data to provide a competitive advantage to a team or individual player. By using data, an analyst can make suggestions on strategies for a given game, monitor the performance of a player, and provide quick analysis of potentially record-setting activities. Sports analytics focuses on two areas: on-field and off-field. The on-field analysis helps improve the tactics and fitness of players, while the off-field analysis focuses on the business and merchandising aspect of sports. Sports analytics is also used in sports gambling to help casinos and similar companies decide on which odds to offer to customers.

What is sports analytics?

Sports analytics refers to the use of data and statistical methods to analyze athletic performance, strategies, and business operations within the sports industry. Professionals in this field collect and interpret data to help teams make informed decisions about player recruitment, game tactics, injury prevention, and fan engagement. The insights gained from sports analytics can provide a competitive edge and drive improvements both on and off the field. With advances in technology, the scope of sports analytics has expanded to include machine learning, video analysis, and wearable devices.

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

To thrive as a Sports Analyst, you need strong statistical analysis skills, a solid understanding of sports rules and strategies, and often a degree in statistics, data science, or a related field. Familiarity with analytics software such as R, Python, SQL, and sports-specific databases is typically expected. Attention to detail, critical thinking, and effective communication help interpret complex data and present actionable insights to coaches and teams. These capabilities are vital for making data-driven decisions that improve team performance and competitive edge.

How does a sports analytics professional typically collaborate with coaches and athletes to influence game strategies?

Sports analytics professionals work closely with coaches and athletes by providing data-driven insights that inform tactical decisions and player development. They often translate complex statistical findings into actionable recommendations, such as identifying strengths and weaknesses or optimizing lineups. Effective collaboration requires strong communication skills and the ability to tailor analyses to the team's goals, ensuring that data supports real-time decision-making and long-term strategy. Regular meetings, presentations, and feedback sessions are common to ensure alignment between analytics staff and on-field personnel.

What is the difference between Sports Analytics vs Sports Data Analyst?

AspectSports AnalyticsSports Data Analyst
CredentialsDegree in statistics, data science, sports managementDegree in statistics, data science, sports management
Work EnvironmentResearch, modeling, strategic planning in sports organizationsData collection, analysis, reporting for teams and organizations
Industry UsageUsed for performance optimization, game strategy, player evaluationUsed for data reporting, insights, and performance tracking

Sports Analytics and Sports Data Analysts share similar educational backgrounds and work environments, focusing on data-driven decision making in sports. While Sports Analytics often involves developing models and strategic insights, Sports Data Analysts primarily focus on collecting and reporting data. Both roles are essential in sports organizations, but Sports Analytics tends to have a broader scope in strategic planning and predictive modeling.

How do I get into sports analytics?

To pursue a career in sports analytics, develop strong skills in statistics, data analysis, and programming languages such as Python or R. Gaining experience through internships, building a portfolio of projects, and understanding sports data sources can improve your prospects; a background in sports management or related fields is also beneficial.

What are careers in sports analytics?

Careers in sports analytics involve analyzing data to evaluate player performance, team strategies, and game outcomes. Professionals typically use statistical software, programming languages like Python or R, and possess strong knowledge of sports and data analysis techniques. Common roles include sports analyst, data scientist, and performance analyst, often requiring a background in statistics, computer science, or related fields.

Will sports analytics jobs be replaced by AI?

Sports analytics jobs involve analyzing data to inform team strategies and player performance, requiring skills in statistics, programming, and domain knowledge. While AI tools can automate data processing and generate insights, human expertise remains essential for interpreting results and making strategic decisions, so these roles are likely to evolve rather than be fully replaced.
More about Sports Analytics jobs

What are the most commonly searched types of Sports Analytics jobs in Seattle, WA?

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

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

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

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

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

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

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

Sports Analytics jobs near you
Infographic showing various Sports Analytics job openings in Seattle, WA as of August 2026, with employment types broken down into 17% Internship, 66% Full Time, and 17% Part Time. Highlights an 66% In-person, 17% Hybrid, and 17% Remote job distribution, with an average salary of $142,625 per year, or $68.6 per hour.

Senior Looker Developer - Analytics Migration, Delivery

Jobtailor

Seattle, WA • On-site

$120 - $160/hr

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Responsibilities
  • Design, develop, and maintain LookML models, views, explores, and Looker dashboards to client coding and quality standards
  • Architect scalable LookML structures that support cross-domain reporting across multiple business verticals
  • Conduct code reviews for offshore developers; enforce standards and best practices before client-facing delivery
  • Optimize Looker report and query performance — identify bottlenecks, tune PDTs, and improve dashboard load times
  • Lead migration of legacy reports to Looker; own requirements analysis, LookML build, UAT support, and sign-off
  • Partner with offshore Analysts to distribute and track migration workload against sprint deadlines
  • Validate migrated reports against source data and business logic; document deviations and business owner approvals
  • Maintain migration tracker, flag blockers, and provide weekly status to PM
  • Work hands-on with client data — manage large numbers of data sources, assess data quality, and proactively partner with client IT/data engineering teams to resolve issues
  • Translate complex data models and technical constraints into clear, understandable language for business stakeholders and presentations
  • Support data governance, security, and access control implementation within Looker
  • Collaborate with client analytics engineers on BigQuery data model design and optimization
  • Serve as the primary Looker standards resource for the EXL offshore team — build internal documentation, review checklists, and training materials
  • Support onboarding of new Looker developers into client coding standards and development workflows
  • Contribute to EXL's internal Looker practice — reusable patterns, accelerators, and peer knowledge transfer
Requirements
  • 8+ years of overall analytics / BI experience, with 5+ years hands‑on in Looker — LookML, dashboards, explores, and SQL queries
  • Master's or bachelor's degree in mathematics, statistics, economics, computer engineering, or a related analytics field; strong academic record preferred
  • Strong expertise in data modeling, SQL, and ETL concepts — ability to independently diagnose and resolve complex data issues
  • Hands‑on experience with performance tuning and optimization of Looker reports and queries
  • Experience with Google Cloud Platform (GCP) and BigQuery, or equivalent cloud data warehouse
  • Extremely comfortable working with data — managing large numbers of data sources, analyzing data quality, and proactively working with client data/IT teams to resolve issues
  • Ability to reformulate highly technical information into concise, understandable terms for presentations and business audiences
  • Very strong analytical and problem‑solving skills; demonstrated ability to research and make decisions on complex day‑to‑day and customer problems
  • Excellent communication skills — written and verbal
  • Experience with version control systems (Git) for LookML development
  • Understanding of data governance, security, and access control within Looker
  • Experience migrating from Tableau, MicroStrategy or other legacy BI platforms to Looker
  • Domain experience in Retail, Media, Aviation, or Sports analytics
  • Prior experience in analytics‑based consulting
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