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Entry Level Sports Statistician Jobs (NOW HIRING)

OCLC, Inc.

Associate Data/ Metadata Analyst

Dublin, OH · On-site

  • Medical

  • Retirement

Free use of our on-site fitness center, gym sports, group exercise classes, and game room * Onsite ... This entry-level role combines metadata expertise with developing technical skills in scripting ...

Ohio University

Lifeguard

Athens, OH · On-site

$14.03/hr

Roles are entry-level and aimed at providing exposure to workplace environments. Supervisory ... Statistics To view the Clery Act Annual Safety and Fire Report Click Here

Collier County, FL

Opioid Program Manager

Naples, FL · On-site

$58K - $95K/yr

The salary listed in the reflects the full pay range for this position, from entry level through ... Prepares related statistical summaries and narrative reports. * Receives and responds to requests ...

Ohio University

Lifeguard

Athens, OH · On-site

$14.03/hr

Roles are entry-level and aimed at providing exposure to workplace environments. Supervisory ... Statistics To view the Clery Act Annual Safety and Fire Report Click Here

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Entry Level Sports Statistician information

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$50.5K

$86.9K

$116.5K

How much do entry level sports statistician jobs pay per year?

As of Aug 15, 2026, the average yearly pay for entry level sports statistician in the United States is $86,921.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $98,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level sports statistician?

To thrive as an Entry Level Sports Statistician, you need a solid understanding of sports rules, basic statistical concepts, and attention to detail, often supported by a relevant degree or coursework in statistics or math. Familiarity with data entry software, spreadsheet tools like Microsoft Excel, and sometimes specialized sports analytics platforms is typically required. Strong observational skills, time management, and effective communication help you accurately record and relay in-game data under time pressure. These skills and qualities are essential for ensuring the integrity and reliability of sports statistics, which inform team strategies and media reporting.

Are entry level sports statisticians in demand?

Entry level sports statisticians are in moderate demand, especially as sports organizations and media outlets increasingly rely on data analysis and advanced statistics. Skills in data management, statistical software, and a strong understanding of sports are valuable for entry-level roles, which often serve as a foundation for career growth in sports analytics.

How do I become an entry level sports statistician?

To become an entry level sports statistician, you typically need a bachelor's degree in statistics, mathematics, sports management, or a related field. Developing skills in data analysis, proficiency with statistical software, and understanding sports performance metrics are important; internships or volunteer work can also provide valuable experience.

What are some common challenges faced by entry level sports statisticians, and how can they be addressed?

Entry level sports statisticians often face challenges such as quickly and accurately recording complex game data in real time, adapting to fast-paced environments, and learning to use specialized statistical software. To address these challenges, it's helpful to practice with mock games, familiarize yourself with the rules of the sport, and seek mentorship from experienced statisticians. Collaborating closely with broadcast teams and coaches also enhances accuracy and helps develop strong communication skills.

What is the difference between Entry Level Sports Statistician vs Sports Data Analyst?

AspectEntry Level Sports StatisticianSports Data Analyst
Required CredentialsBachelor's in Sports Management, Statistics, or related fieldBachelor's in Data Science, Statistics, or related field
Work EnvironmentSports teams, athletic organizations, sports mediaSports organizations, analytics firms, media companies
Employer & Industry UsageUsed mainly in sports teams and leagues for player and game analysisUsed across sports industry for performance, marketing, and strategic insights

While both roles involve analyzing sports data, an Entry Level Sports Statistician primarily focuses on collecting and interpreting game and player statistics within sports teams or organizations. A Sports Data Analyst often has a broader scope, including advanced data modeling and insights for strategic decisions across various sports-related industries.

What is an entry level sports statistician?

Entry level sports statisticians are professionals who collect, record, and analyze data related to sports events and athletes’ performances. They typically work for sports teams, media outlets, or data analytics companies, helping to ensure that accurate statistics are available for use in broadcasts, reports, and team decision-making. Their responsibilities may include tracking player stats during games, compiling reports, and maintaining databases. This role is ideal for individuals with strong attention to detail and an interest in both sports and data analysis.
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Entry Level Sports Statistician jobs near you
Infographic showing various Entry Level Sports Statistician job openings in the United States as of August 2026, with employment types broken down into 6% As Needed, 44% Full Time, 44% Part Time, and 6% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $86,921 per year, or $41.8 per hour.

Associate Data/ Metadata Analyst

OCLC, Inc.

Dublin, OH • On-site

Full-time

Medical, Retirement

Posted 4 days ago

Job description

Together we make breakthroughs possible.
At OCLC, we build technology with a purpose: to connect libraries and make knowledge accessible worldwide, because we believe that what is known must be shared. Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and other technologies that connect people and organizations to the information they need. We value the power of unique perspectives and experiences to unlock innovation. At OCLC, your ideas matter, whether you have two years of experience or 20. You'll learn, create, and problem-solve with technologists, product developers, librarians, researchers, marketing pros, and support teams around the world.
Why join OCLC?
OCLC is consistently recognized as a best place to work by several independent programs. We recognize and reward people and results with a comprehensive Total Rewards package. This means competitive compensation that reflects your unique contributions-performance, experience, and skills-along with exceptional benefits, including best-in-class health coverage, retirement plans with generous company contributions, and a commitment to your overall well-being.
  • We know the best ideas don't always happen at a desk. Take a walking meeting around our 100-acre campus or enjoy lunch on the patio. We're committed to your success-both personally and professionally. Hybrid work environment: For many roles, three days a week on-site, with occasional additional days based on business needs.
  • Free use of our on-site fitness center, gym sports, group exercise classes, and game room
  • Onsite catering and cafeteria subsidized by OCLC
  • Health and wellness events
  • Work environments with individual and team spaces and the latest technology tools
  • Paid parental leave and adoption assistance
  • Tuition reimbursement and Public Service Loan Forgiveness eligibility
  • Company-subsidized pricing on local tickets and memberships

Join us in transforming how people everywhere access information and be part of a mission-driven team that makes a global impact.
The job details are as follows:
The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings data, ensuring accuracy and integrity through evaluation, transformation, and maintenance. This entry-level role combines metadata expertise with developing technical skills in scripting, automation, and AI-assisted workflows. Working under regular supervision, the Associate will transition from executing well-defined tasks to taking ownership of complex data projects. This is an opportunity to develop expertise at the intersection of library data, modern data engineering, and emerging AI - in a team that invests in the growth of its people.
Responsibilities:
Data Operations & Quality
  • Data Lifecycle Management: Perform data ingest, normalization, enrichment, and matching according to established standards (e.g., MARC, KBART).
  • Quality Assessment: Profile incoming data to identify and resolve structural issues, encoding errors, and tagging discrepancies.
  • Troubleshooting: Investigate and resolve data quality issues, escalating complex problems to senior staff as needed.
  • Vendor Communication: Coordinate with external data providers and partner institutions regarding routine data specifications and quality issues.
Technical Solutions & Automation
  • Pipeline Support: Apply existing scripts and automated workflows to process data; identify inefficiencies and suggest process improvements.
  • Data Visualization: Use and interpret dashboards (e.g., Power BI) to monitor data quality trends and communicate findings.
  • AI Integration: Utilize AI-assisted tools for record matching and field mapping; contribute structured feedback that helps improve AI model accuracy over time.
Collaboration & Documentation
  • Knowledge Management: Document data source profiles, processing decisions, and technical workflows to ensure team-wide knowledge sharing.
  • Team Support: Execute foundational tasks to support senior analysts and participate in platform improvement projects.

Minimum Required Knowledge, Skills and Experience:
  • Bachelor's degree in computer science, math, statistics, or related field and internship experience with data analysis or creation of library data.
  • Entry-level analytical and communication skills, with attention to data quality while working under regular supervision.

Preferred Knowledge, Skills and Experience:
  • Metadata Standards: Foundational knowledge of MARC, Dublin Core, KBART, or BIBFRAME.
  • Technical Tools: Exposure to scripting languages (Python, SQL, or XSLT) and data transfer protocols (SFTP, APIs, or AWS S3).
  • Data Platforms: Conceptual familiarity with cloud data stores (e.g., Snowflake) and visualization tools (e.g., Power BI, Streamlit).
  • Emerging Tech: Interest in applying AI and linked data concepts (e.g., Schema.org) to library data challenges.

Working Conditions: Normal office environment.
ADA/EAA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.

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