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Data Analytics Sports Jobs in Reston, VA (NOW HIRING)

Socket.dev

Data Scientist I

Alexandria, VA · On-site

$90 - $110/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Data Scientist I Location: Alexandria, VA Work Environment: Onsite Clearance Required: Secret is ... sports, or other military settings. * Strong technical and analytical skills in the following:

Sun & Ski Sports

Hardgoods Coordinator

Falls Church, VA · On-site

$15 - $19/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Create and implement strategic plans to increase department sales using data analysis and goal ... Represent and promote Sun & Ski Sports within the local cycling and snow sports communities.

Events DC

Business Analyst

Washington, DC · On-site

Subject matter expert on items for industry analytics and reports and other forecasting data, Oracle, Momentus and other relevant sports, entertainment and venue reporting. * Utilize both syndicated ...

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All JobsData Analytics Sports JobsData Analytics Sports Jobs in Reston, VA

Data Analytics Sports information

Can a data analyst become a sports analyst?

A data analyst can become a sports analyst by applying their skills in data collection, statistical analysis, and visualization to sports data. Transitioning may require knowledge of sports-specific metrics, industry terminology, and familiarity with tools like SQL, Excel, or sports analytics software. Additional experience or certifications in sports analytics can facilitate this career shift.

What skills and qualifications are needed to thrive as a data analytics sports professional?

To thrive as a Data Analytics Sports professional, you need strong statistical analysis skills, a background in mathematics or data science, and familiarity with sports industry metrics. Proficiency with data visualization tools (like Tableau), programming languages (such as Python or R), and sports analytics software is typically required. Analytical thinking, attention to detail, and strong communication skills set top performers apart in this field. These skills are crucial for transforming complex data into actionable insights that enhance team performance and inform strategic sports decisions.

What does a data analyst do in sports?

A data analyst in sports collects, processes, and interprets data related to player performance, team statistics, and game outcomes. They use tools like Excel, SQL, and data visualization software to identify trends and support strategic decisions for teams and organizations.

Do NFL teams hire data analysts?

Yes, NFL teams often hire data analysts to evaluate player performance, develop strategies, and improve decision-making using statistical tools and data analysis techniques. These roles typically require skills in data management, programming, and sports analytics software, and may involve working closely with coaching staff and management.

What are common challenges faced by data analysts in the sports industry, and how can they be addressed?

Data analysts in the sports industry often encounter challenges such as integrating disparate data sources (e.g., player stats, wearable tech, and video analysis), ensuring data accuracy, and translating findings into actionable insights for coaches and management. Addressing these challenges requires strong technical skills, effective communication, and a collaborative approach with IT, coaching staff, and sports scientists. Staying updated with the latest analytics tools and maintaining clear documentation can also help streamline workflows and improve decision-making across teams.

What is the difference between Data Analytics Sports vs Data Analysis in Finance?

AspectData Analytics SportsData Analysis in Finance
Required CredentialsBachelor's in Sports Management, Data Science, or related fields; certifications like SAS or TableauBachelor's in Finance, Economics, or related fields; certifications like CFA, CPA
Work EnvironmentSports teams, leagues, sports analytics firms, media companiesBanks, investment firms, financial institutions, corporate finance departments
Employer & Industry UsageUsed to improve team performance, player stats, fan engagementUsed for risk assessment, investment decisions, financial forecasting

Data Analytics Sports focuses on analyzing sports-related data to enhance team performance and fan engagement, while Data Analysis in Finance centers on financial data to inform investment and business decisions. Both roles require strong analytical skills and data tools but serve different industries and objectives.

What is a data analytics sports professional?

Data analytics sports jobs involve using data analysis techniques to help sports teams, organizations, or media companies make better decisions. Professionals in this field collect, process, and interpret data related to player performance, game strategy, fan engagement, and business operations. They use statistical tools, programming languages, and visualization software to turn raw data into actionable insights. These roles are vital for gaining a competitive edge, optimizing team performance, and enhancing fan experiences in the sports industry.
What job categories do people searching Data Analytics Sports jobs in Reston, VA look for? The top searched job categories for Data Analytics Sports jobs in Reston, VA are:
What cities near Reston, VA are hiring for Data Analytics Sports jobs? Cities near Reston, VA with the most Data Analytics Sports job openings:
Data Analytics Sports jobs near you
Infographic showing various Data Analytics Sports job openings in Reston, VA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Basketball Data Analyst (Mystics)

Monumental Sports & Entertainment

Washington, DC • On-site

$110K - $130K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Position Overview:

The Washington Mystics Basketball Data Analyst is responsible for designing, testing, and building statistical models and reports to support the Mystics. This position will be an integral component of research efforts and be a member of a dynamic team consisting of programmers, developers, statisticians, analysts, and data scientists. This role will work closely on projects impacting the decision-making process for the Washington Mystics alongside the front office.

Are you creative and have a passion for exploring, inventing and discovering new insights about basketball and data communication?! We'd love to hear from you!

Responsibilities:
  • Build and develop systems, analytical models, foundational structures, and machine learning models to support decision-making processes for the Mystics.
  • Respond in a timely and efficient manner to ad-hoc requests from Basketball Operations Executives and the front office.
  • Translate data-driven results into actionable basketball decisions and recommendations.
  • Use data to identify possible solutions to strategic questions, including areas of player evaluation, game management, in-game tactics, roster building, salary cap strategy, and broader WNBA league trends.
  • Integrate novel research, basketball metrics, and models into existing and new applications.
  • Originate innovative ways to analyze and summarize data from existing and new partners.
  • Provide the basketball operations departments with the best empirical data and data analysis available, ensuring objectivity and integrity of information through meticulous analytical models.
  • Work with the larger research team to maintain a multidimensional and secure information system that anticipates the needs of the front office.
  • Other duties as assigned.
Minimum Qualifications:
  • Bachelor's Degree or equivalent experience in STEM field including Statistics, Mathematics, Computer Science, Data Science, or similar domain.
  • Basic knowledge of WNBA, team rosters, and league trends.
  • Experience with basketball data, including play-by-play and sports tracking data such as Second Spectrum markings or raw data.
  • Experience with standard SQL and other database management tools.
  • Experience using Python, R, or other statistical programming languages.
  • Experience with data visualization principles and tools.
  • Excellent analytical skills with experience researching and analyzing data.
  • Outstanding written and verbal communication skills.
  • High integrity, dependable, and comfortable with confidential information.
  • Ability to effectively prioritize tasks and manage time efficiently.
  • Flexibility to work evenings, weekends, and holidays as needed.

Pay Range: $110k - 130k USD.

Benefit Eligibility: This role is eligible to participate in health and welfare benefits.

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