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Freelance Sports Data Collection Jobs (NOW HIRING)

The Sports Scientist will design and manage data collection, storage, and reporting systems to optimize development, performance, rehabilitation, and talent identification processes. This role ...

Data Engineer

$117K - $140K/yr

We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs ... You'll collaborate closely with our MLOps , LLMOps , and Sports Data teams to ensure seamless ...

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Freelance Sports Data Collection information

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$14

$47

$132

How much do freelance sports data collection jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for freelance sports data collection in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is the difference between Freelance Sports Data Collection vs Freelance Sports Writer?

AspectFreelance Sports Data CollectionFreelance Sports Writer
CredentialsBasic knowledge of sports statistics, data entry skillsWriting skills, sports knowledge, possibly journalism background
Work EnvironmentRemote, data-focused tasks, often using specialized softwareRemote or on-site, writing articles, blogs, or reports
Employer & Industry UsageSports analytics companies, media outlets, betting firmsMedia outlets, sports websites, magazines

Freelance Sports Data Collection involves gathering and inputting sports statistics, focusing on accuracy and data management. Freelance Sports Writers create content, articles, and reports about sports events. While both roles require sports knowledge, data collection emphasizes technical skills, whereas writing emphasizes communication and storytelling.

What are some common challenges faced by freelance sports data collectors, and how can they be addressed?

Freelance sports data collectors often face challenges such as working irregular hours, dealing with fast-paced environments during live events, and ensuring data accuracy under pressure. To address these challenges, it's important to develop strong time-management skills, familiarize yourself with the sport’s rules, and practice using data entry tools before events. Building a network with other data collectors can also provide support and tips for handling tricky situations. Being adaptable and proactive in communicating with event coordinators can further help ensure smooth data collection.

What are the key skills and qualifications needed to thrive as a Freelance Sports Data Collector, and why are they important?

To thrive as a Freelance Sports Data Collector, you need strong attention to detail, knowledge of sports rules and statistics, and often a background in data entry or sports analytics. Familiarity with mobile data collection apps, statistical software, and sometimes official accreditation from sports organizations is typically required. Excellent observational skills, reliability, and the ability to work independently under tight deadlines help individuals stand out in this role. These skills ensure accurate, timely data collection, which is critical for sports analytics, reporting, and betting industries.

What is freelance sports data collection?

Freelance sports data collection involves gathering and recording statistics and information about sports events on a contract or per-project basis. Freelancers may attend games in person or collect data remotely, depending on the assignment. The data can include scores, player statistics, play-by-play actions, and other relevant metrics that are valuable to sports organizations, media outlets, and analytics companies. This work requires attention to detail, a strong understanding of the sport, and the ability to work independently. Freelance sports data collectors often use specialized software or platforms to submit their data in real time.
More about Freelance Sports Data Collection jobs
What cities are hiring for Freelance Sports Data Collection jobs? Cities with the most Freelance Sports Data Collection job openings:
What are the most commonly searched types of Sports Data Collection jobs? The most popular types of Sports Data Collection jobs are:
What states have the most Freelance Sports Data Collection jobs? States with the most job openings for Freelance Sports Data Collection jobs include:
Infographic showing various Freelance Sports Data Collection job openings in the United States as of May 2026, with employment types broken down into 100% Part Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Senior Product Manager, Data Platform

Genius Sports

Los Angeles, CA

$136K - $179K/yr

Other

Posted 3 days ago


Job description

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before.Learn more at geniussports.com.

The Role -  Senior Product Manager
We are seeking a Senior Product Manager to join our Data & AI team and lead product strategy for the platform capabilities that power the ingress, transformation, storage, and egress of highly granular, live sports data. 

The ideal candidate combines strong product instincts with deep platform thinking and technical fluency in real-time data systems. You should be equally comfortable defining long-term strategy, rationalizing legacy tooling, partnering with engineers on highly scalable data platforms, and enabling downstream analytics, AI, and API products. 

Responsibilities:  

This role sits at the center of our sports data ecosystem. You will work across Sports Tech, Data Collection, Engineering, BI, Data Science, Betting, Fan Engagement, Advertising, and commercial stakeholders to build the shared tools and platforms that capture, process, analyze, and distribute real-time team- and player-level sports data at scale.   You will play a key role in one or more of the following areas:   

Maintain and Modernize Data Pipelines 

  • Identify, assess, and prioritize new data sources for onboarding, including fixtures data, odds data, player and match data, product usage data, customer data, and other relevant internal and external datasets.
  • Partner with data owners and engineering teams to understand available attributes, business value, integration methods, and operational considerations for each source.
  • Work with engineering to define, build, and evolve a robust, real-time data platform capable of ingesting, aggregating, transforming, and exposing terabytes of sports, betting, customer, and product intelligence data.
  • Partner with engineering to design and implement scalable data cleaning, normalization, and transformation processes that improve data consistency, usability, and compliance.
  • Drive requirements for end-to-end monitoring, alerting, observability, and reporting to ensure highly available, low-latency, and performant data processing across the platform.
  • Ensure ETL design, schema management, storage, and retention practices align with internal best practices as well as security and privacy standards. 

Enable Data Warehousing, Reporting, and Advanced Analytics 

  • Work closely with stakeholders across marketing, business intelligence, customer intelligence, product planning, and other functions to understand business needs and make data accessible for analysis and decision-making.
  • Partner with BI and analytics teams to deliver self-serve reporting capabilities, including dashboards, semantic layers, cubes, and other tools that broaden access to customer and product intelligence.
  • Support the evaluation and integration of advanced analytical tools and data workflows that enable data scientists and analysts to model customer behavior, generate predictive insights, and inform betting and personalized fan engagement use cases.
  • Help define the data foundations needed to support AI and machine learning use cases across the business. 

Build, Maintain, and Evolve Data Distribution Tools 

  • Partner with stakeholders across sports betting, fan engagement, advertising, leagues, and teams to understand their data consumption needs and deliver scalable distribution capabilities.
  • Own the API and data distribution product strategy and roadmap, ensuring alignment with key internal and external stakeholders.
  • Define and prioritize user stories and backlog items related to data sharing, API access, entitlements, delivery mechanisms, and partner integrations.
  • Support the development of push- and pull-based distribution patterns that make data available reliably and efficiently across a range of products and customers.
  • Partner with Advertising and Genius Marketing Suite stakeholders to enable audience management, segmentation, and targeting capabilities that power personalized advertising and fan experiences at scale. 

Lead Product Strategy and Cross-Functional Execution 

  • Create clear product strategies, roadmaps, requirements, and success metrics for core data platform capabilities.
  • Balance immediate business needs with long-term platform investments, technical debt reduction, and architectural evolution.
  • Act as the connective tissue between business stakeholders, operational teams, and technical teams to ensure shared understanding and effective execution.
  • Use data, customer feedback, and operational insights to prioritize investments and continuously improve platform reliability, usability, and value. 

Qualifications:  

  • Significant product management experience, with meaningful experience owning data platform, infrastructure, API, or enterprise platform products. 
  • Strong understanding of real-time data systems, data pipelines, ETL/ELT, data warehousing, APIs, and large-scale distributed platforms.  
  • Experience working closely with engineering teams to deliver complex technical products and platform capabilities.  
  • Demonstrated ability to define product strategy and execute in cross-functional environments with multiple stakeholders and competing priorities.  
  • Strong analytical and problem-solving skills, with the ability to evaluate data sources, define business value, and make sound prioritization decisions.  
  • Excellent written and verbal communication skills, including the ability to translate between technical and non-technical audiences.  
  • Experience building or supporting products related to analytics, BI, machine learning, or AI-enabled use cases.  
  • Comfort operating in fast-paced environments where reliability, scalability, latency, and data quality are business-critical. 
  • Familiarity with live event data collection workflows, including operator-assisted and computer-vision-driven systems.  
  • Experience with modern data platform technologies, streaming architectures, observability tooling, and cloud-based data ecosystems.  
  • Exposure to identity, segmentation, personalization, or customer intelligence platforms.  
  • Experience managing legacy platform modernization and migration programs. 

The salary for this role is based on an annualized range of $165,000 - $200,000. This role will also be eligible to take part in Genius Sports Group's benefits plan. 

As well as a competitive salary and range of benefits, we're committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports  
One team, being brave, driving change 
We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports.  
Let us know when you apply if you need any assistance during the recruiting process due to a disability. 


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