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Full Time Sports Data Collection Jobs (NOW HIRING)

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$145K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Telus Digital

Project Manager, Onsite Data Collection

$104K - $131K/yr

... full-time, part-time, and crowd-based collectors. * Drive consistency and performance across ... Familiarity with robotics or data collection programs preferred. * Proficiency with Google ...

Telus Digital

Project Manager, Data Collection Delivery

$123K/yr

... full-time, part-time, and crowd-based collectors. * Drive consistency and performance across ... Familiarity with robotics or data collection programs preferred. * Proficiency with Google ...

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Full Time Sports Data Collection information

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How much do full time sports data collection jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for full time sports data collection in the United States is $25.31, according to ZipRecruiter salary data. Most workers in this role earn between $23.32 and $25.96 per hour, depending on experience, location, and employer.

What is full time sports data collection?

Full time sports data collection involves gathering, recording, and analyzing data related to sports events, teams, and players on a full-time basis. This can include tracking statistics such as scores, player performance, injuries, and other relevant metrics during live games or through video analysis. Professionals in this role often work for sports organizations, analytics companies, or media outlets, providing essential information for coaches, analysts, and fans. The job may require strong attention to detail, familiarity with sports rules, and proficiency with data entry or analytics software.

What does a typical day look like for someone working in full time sports data collection?

A typical day in full-time sports data collection often involves arriving at sporting events or logging into live feeds to record and verify data points such as scores, player statistics, and key game events in real-time. The role usually requires working as part of a larger data team, with clear protocols for data accuracy and communication. Collaboration with analysts, editors, and sometimes with on-site event staff is common to ensure the integrity of the information. Schedules can vary, often including evenings and weekends depending on the sports calendar, and attention to detail as well as adaptability to fast-paced environments are critical for success.

What are the key skills and qualifications needed to thrive as a full time sports data collection specialist?

To excel as a Full Time Sports Data Collection Specialist, you need strong analytical skills, attention to detail, and a solid understanding of sports rules and statistics, often supported by a relevant degree or prior experience. Familiarity with data collection software, spreadsheets, and sometimes real-time data entry systems is typical for the role. Excellent communication, adaptability, and reliability are important soft skills for working under pressure and collaborating with teams or event staff. These capabilities ensure accurate and timely data reporting, which is crucial for stakeholders relying on real-time sports information.

What is the difference between Full Time Sports Data Collection vs Part Time Sports Data Collection?

AspectFull Time Sports Data CollectionPart Time Sports Data Collection
CredentialsTypically requires basic sports data knowledge, sometimes certificationsSimilar credentials, often less experience needed
Work EnvironmentFull-time hours, regular schedule, often in sports venues or officesFlexible hours, part-time shifts, may work remotely or on-site
Employer & Industry UsageEmployed by sports leagues, data companies, or media outletsFreelance or contract roles, used by smaller organizations or for supplemental income

Full Time Sports Data Collection involves regular hours, consistent employment, and often more responsibilities, while Part Time Sports Data Collection offers flexible scheduling and is suitable for those seeking supplemental income or flexible work arrangements. Both roles require similar skills and credentials but differ mainly in hours and employment structure.

More about Full Time Sports Data Collection jobs

What cities are hiring for Full Time Sports Data Collection jobs?

Cities with the most Full Time 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 job categories do people searching Full Time Sports Data Collection jobs look for?

The top searched job categories for Full Time Sports Data Collection jobs are:

Full Time Sports Data Collection jobs near you
Infographic showing various Full Time Sports Data Collection job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $52,640 per year, or $25.3 per hour.

Data Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$160K/yr

Full-time

Re-posted yesterday

Job description

Company Overview
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties
  • Support production systems and help triage issues during live sporting events
  • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
  • Build new sports betting data products and predictions offerings
  • Integrate large and complex real-time datasets into new consumer and enterprise products
  • Develop production-level predictive analytics into enterprise-grade APIs
  • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Requirements
  • BS/BA degree in Mathematics, Computer Science, or related STEM field
  • Minimum of 2+ years of demonstrated experience writing production level code (Python)
  • Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow
  • Demonstrated experience with Kubernetes
  • Experience building end-to-end ETL pipelines
  • Experience utilizing REST APIs
  • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
  • Experience with web scraping and cleaning unstructured data
  • Knowledge of data science and machine learning concepts
  • A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets

Base Salary: Starting at $160,000 - DOE
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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