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Sports Data Jobs (NOW HIRING)

Genius Sports

AI Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

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 ...

Genius Sports

AI Engineer

Los Angeles, CA

$123K - $148K/yr

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 ...

Paramount

Sr Lead Product Manager

Fort Lauderdale, FL · On-site

$120K - $159K/yr

You will shape how real-time sports data moves from source systems into the fan experiences that define game day, from scores and stats to betting-adjacent and insight-rich product surfaces across ...

Paramount

Sr Lead Product Manager

Manhattan, NY

$139K - $183K/yr

You will shape how real-time sports data moves from source systems into the fan experiences that define game day, from scores and stats to betting-adjacent and insight-rich product surfaces across ...

Boyd Gaming

Race and Sports Hub Coordinator

Las Vegas, NV

$15.25 - $19.75/hr

Assists Supervisors with data entry, research and reporting * Assists Supervisors with line changes ... Works front line of Race and Sports book when necessary * Provides excellent customer service

Boyd Gaming

Race and Sports Hub Coordinator

Las Vegas, NV · On-site

$15.25 - $19.75/hr

Assists Supervisors with data entry, research and reporting * Assists Supervisors with line changes ... Works front line of Race and Sports book when necessary * Provides excellent customer service

Pentasia

MLB Data Entry Gig (Miami Marlins)

Miami, FL · On-site

$15.25 - $19.75/hr

Sports Data & Analytics Are you a baseball fan based near Miami, FL? Our client is hiring sports enthusiasts to attend Miami baseball games in Miami to input real-time play-by-play data using their ...

Paramount

Sr Lead Product Manager

Burbank, CA · On-site

$134K - $177K/yr

You will shape how real-time sports data moves from source systems into the fan experiences that define game day, from scores and stats to betting-adjacent and insight-rich product surfaces across ...

Paramount

Sr Lead Product Manager

Fort Lauderdale, FL · On-site

$120K - $159K/yr

You will shape how real-time sports data moves from source systems into the fan experiences that define game day, from scores and stats to betting-adjacent and insight-rich product surfaces across ...

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

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 ...

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

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 ...

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

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 ...

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Sports Data information

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$10

$34

$63

How much do sports data jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for sports data in the United States is $34.95, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $56.97 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Sports Data position, and why are they important?

To thrive in Sports Data, you need strong analytical skills, a background in statistics or data science, and a solid understanding of sports rules and analytics. Familiarity with data visualization tools (such as Tableau or Power BI), coding languages (like Python or R), and sports data platforms is typically expected. Attention to detail, effective communication, and the ability to quickly interpret and present findings are valuable soft skills for this role. These competencies are crucial for delivering accurate insights and supporting decision-making in the fast-paced sports industry.

What are typical daily responsibilities for a Sports Data professional?

A Sports Data professional typically spends their day gathering, cleaning, and analyzing sports-related datasets, such as player statistics, game outcomes, or performance metrics. They often create reports or dashboards, use statistical models to identify trends, and present actionable insights to coaching staff, management, or broadcasting teams. Collaboration is common with analysts, coaches, and IT teams to ensure data accuracy and relevance. Maintaining data integrity and keeping up with the latest sports analytics tools are also key parts of the role.

What is a Sports Data job?

A Sports Data job involves collecting, analyzing, and interpreting sports-related statistics to provide insights for teams, media, bookmakers, and fans. Professionals in this field work with data from games, player performances, and team statistics to identify trends and patterns. Roles can include data analysts, statisticians, scouts, and developers who create models to predict outcomes. These jobs require strong analytical skills, statistical knowledge, and proficiency in tools like Excel, SQL, Python, or R.

More about Sports Data jobs
What cities are hiring for Sports Data jobs? Cities with the most Sports Data job openings:
What are the most commonly searched types of Sports Data jobs? The most popular types of Sports Data jobs are:
What states have the most Sports Data jobs? States with the most job openings for Sports Data jobs include:
What job categories do people searching Sports Data jobs look for? The top searched job categories for Sports Data jobs are:
Sports Data jobs near you
Infographic showing various Sports Data job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $72,704 per year, or $35 per hour.

AI Engineer

Genius Sports

Los Angeles, CA • On-site

$123K - $148K/yr

Full-time

Posted 15 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.
About the Role - AI Engineer, Sports AI
We're looking for an AI Engineer on our Sports AI team to help build the next generation of applied AI systems powering sports analysis, automation, and insights.
These systems use live and historical sports data, including tracking data, structured feeds, broadcast video, commentary, and text, to understand game context, detect & enrich key events, estimate the probability of future events, and generate insights. The outputs from these systems power a range of products and workflows, such as projecting which games or moments will be most exciting to fans and automating parts of manual play-by-play collection using CV/AI. The role spans a broad set of sports modeling and automation problems across multiple sports, including soccer, American football, and basketball.
This role sits at the intersection of machine learning, AI system design, and production engineering. You'll own scoped AI systems end-to-end: framing the relevant modeling problems, constructing the datasets needed to solve them, training and composing models and algorithms, building the inference pipelines that orchestrate them, and rigorously evaluating output quality against messy, real-world data.
You'll work on challenges like aligning signals across multiple sources, handling uncertainty and inconsistency in system outputs, and improving accuracy, latency, and reliability in real-time production workflows. In this role, hands-on ML/AI work will be central: understanding data, developing models and algorithms, evaluating outputs empirically, and iterating in production. You'll also apply LLMs and agentic workflows as part of your broader AI engineering toolkit.
Key Responsibilities
  • Own applied AI work end-to-end, from data exploration and early prototypes through evaluation, production integration, and iteration
  • Develop and compose models, algorithms, and inference pipelines that convert sports data into structured events, predictions, insights, and confidence-aware outputs
  • Build models for problems such as event detection, event likelihood estimation, fan interest & excitement projection, and automation of manual play-by-play collection
  • Work with messy, multimodal sports data from tracking systems, video and computer vision outputs, audio, commentary, text, and structured feeds, including imperfect labels and ambiguous real-world examples
  • Define and use metrics, evaluation datasets, and benchmarks to measure AI system quality and guide model, algorithm, and product decisions
  • Train, adapt, evaluate, and integrate ML models and AI components, including multi-step systems where model, algorithmic, and LLM/agent outputs are composed, validated, and refined
  • Design workflows that use human review or correction data to improve evaluation, model iteration, and production output quality where appropriate
  • Work closely with CV engineers on training pipelines, labeling workflows, and model deployment patterns
  • Partner with product, data platform, infrastructure, and systems engineers to integrate evaluated AI outputs into real-time sports products and automation workflows
  • Mentor junior teammates and contribute to team knowledge-sharing, reviews, and experiment design

Qualifications
  • 3+ years of experience building production ML, CV, or AI systems
  • Ability to translate ambiguous sports product goals into concrete ML tasks, including defining the prediction target, identifying the right data, measuring output quality, and shipping production-ready solutions
  • Hands-on production ML/AI experience, including constructing datasets, defining features and labels, training and deploying models, evaluating outputs empirically, and shipping AI system capabilities into production
  • Strong modeling judgment across deep learning and classical ML, with experience choosing approaches based on data inputs and problem structure
  • Experience with predictive modeling, event detection, data labeling, data quality improvement, and communicating experiment results to technical and non-technical stakeholders
  • Ability to evaluate AI system quality beyond anecdotal inspection, including reasoning about ambiguous outputs, imperfect labels, uncertainty, and real-world product tradeoffs
  • Strong production engineering fundamentals, including testing, observability, performance, and reliability
  • Demonstrated interest in the fast-moving landscape of LLMs, latest models, agentic AI systems, and development frameworks
  • Comfortable working in fast-moving, iterative environments with evolving requirements

Preferred Qualifications
  • Hands-on experience with LLM-integrated workflows, LLM APIs or cloud AI platforms such as AWS Bedrock, agentic AI systems, multi-agent systems, or evaluation of LLM/agent outputs in production workflows
  • Experience with ML/CV domains relevant to sports understanding, such as action recognition, sequence modeling, multimodal modeling, object detection, tracking, or player identification
  • Experience working with player tracking data, sports analytics, play-by-play data, labeling platforms, and/or ML training platforms such as Union
  • Experience collaborating with CV engineers or integrating CV model outputs into downstream ML workflows
  • Experience using human review or correction workflows to evaluate and improve AI system quality
  • Experience building production systems in Rust
  • Familiarity with streaming, event-driven, audio/video, or real-time data workflows is a plus
  • Background or strong interest in sports, especially soccer, American football, and basketball

The salary for this role is based on an annualized range of $160,000 - $190,000 USD. This role will also be eligible to take part in Genius Sports Group's benefits plan.
We enjoy an 'office-first' culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required.
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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