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Game Analytics Jobs (NOW HIRING)

AEG

Research Engineer (AI + Sports)

Pittsburgh, PA · On-site

YinzCam is seeking exceptional Research Engineers to lead the development of AI-driven video analysis and game analytics systems that power next-generation fan experiences in professional sports.

Rockstar Games

Senior Analytics Engineer

New York, NY · On-site

Rockstar Games is on the lookout for a skilled Senior Analytics Engineer with strong software ... development skills who is passionate about games and big data. This is a full-time, in-office ...

Progressive Gaming

Game Mathematician II

Reno, NV

$70K - $131K/yr

... Analyze market performance data to identify trends and inform future game mechanics Ensure math designs meet jurisdictional requirements and industry standards Qualifications What We're Looking For ...

Mercor

Chess Expert - Game Analyst

New York, NY · Remote

$90/hr

Reconstruct full chess games on an analysis board using corrected transcripts, ensuring completeness and accuracy. * Identify and itemize minimal missing information when transcripts do not uniquely ...

Progressive Gaming

Game Mathematician

Chicago, IL

$70K - $80K/yr

What You Will Do As a Game Mathematician , you will play a key role in shaping the player experience by designing and analyzing the mathematical models behind our games. You will contribute across ...

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How much do game analytics jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for game analytics in the United States is $15.27, according to ZipRecruiter salary data. Most workers in this role earn between $13.46 and $18.27 per hour, depending on experience, location, and employer.

What is game analytics?

Game analytics is the process of collecting, analyzing, and interpreting data generated by players and the game itself to improve gameplay, player experience, and business outcomes. Analysts use data from player interactions, in-game events, and monetization strategies to identify trends, optimize game design, and inform decision-making. Game analytics helps developers understand player behavior, increase retention, and maximize revenue by making data-driven changes.

How do game analytics professionals collaborate with game designers and developers during the game development process?

Game analytics professionals work closely with game designers and developers by providing data-driven insights that inform design decisions, player engagement strategies, and feature prioritization. They analyze player behavior, in-game metrics, and user feedback to identify trends, pain points, and opportunities for improving the gaming experience. Regular meetings and cross-functional teams are common, ensuring that analytics findings directly influence gameplay tweaks, monetization strategies, and updates. This collaborative environment fosters a continuous feedback loop, making analytics an integral part of the entire game development lifecycle.

What are the key skills and qualifications needed to thrive as a game analyst, and why are they important?

To thrive as a Game Analyst, you need a solid background in data analysis, statistical modeling, and a strong understanding of gaming metrics, typically supported by a degree in mathematics, computer science, or a related field. Familiarity with analytical tools like SQL, Python, R, and visualization platforms such as Tableau or Power BI is essential. Strong problem-solving abilities, effective communication, and a passion for gaming help analysts translate data insights into actionable recommendations for game development teams. These skills ensure that game design and business decisions are data-driven, enhancing player experience and maximizing game performance and profitability.

How to become a game analytics professional?

To become a game analytics professional, you typically need a background in data analysis, statistics, or computer science, along with experience using analytics tools like SQL, Excel, or specialized platforms such as Tableau or Power BI. Developing skills in game design, understanding player behavior, and gaining knowledge of game development processes are also beneficial. Earning relevant certifications or degrees can improve job prospects in this field.

What does a game analytics do?

A game analyst collects and interprets data related to player behavior, game performance, and engagement metrics to help developers improve gameplay and retention. They use tools like data visualization software and statistical analysis to identify trends and inform design decisions. Strong analytical skills and knowledge of game development environments are essential for this role.
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Game Analytics jobs near you
Infographic showing various Game Analytics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $31,769 per year, or $15.3 per hour.

Research Engineer (AI + Sports)

YinzCam Inc.

Pittsburgh, PA • On-site

Full-time

Re-posted 7 days ago

Job description

Description
YinzCam is seeking exceptional Research Engineers to lead the development of AI-driven video analysis and game analytics systems that power next-generation fan experiences in professional sports. This is a rare opportunity to conduct publishable research while building products that reach millions of fans in real time.
You'll work at the cutting edge of computer vision and machine learning applied to sports, collaborating with leading academic researchers at Carnegie Mellon University while taking your innovations from prototype to production. This role demands both research rigor and product sensibility. We value publication records and engineering excellence equally. This is a full-time, onsite position based in Pittsburgh, PA.
You will be at the forefront of establishing a new, in-house AI Research Lab within YinzCam, and working with multiple sports teams, leagues, and venues to apply AI to the fan experience and to business operations.
CORE RESPONSIBILITIES.
Video Analysis & Computer Vision
  • Design and develop AI systems for real-time video understanding of live sporting events (player detection, action recognition, spatial analysis, etc.)
  • Build robust computer vision pipelines that handle challenging real-world footage (lighting, occlusion, multiple camera angles)
  • Explore novel architectures and techniques in modern CV to solve sports-specific problems

Large-Scale Game Analytics
  • Develop AI systems to extract, aggregate, and interpret game data at scale across multiple sports, teams, and seasons
  • Create spatial and temporal analytics frameworks that surface actionable insights from video and sensor data
  • Build analytics platforms that scale from single games to league-wide deployments

AI-Powered Fan Experiences
  • Translate video understanding and analytics into engaging, intuitive experiences for millions of fans
  • Collaborate on product features that leverage AI (real-time highlights, personalized stats, interactive visualizations, etc.)
  • Ensure research outputs move through the full product development lifecycle

CORE GOALS.
  1. Publish Your Work: We intend to publish the work coming out of these research projects. Papers will be published in top-tier CV/ML venues and presented at conferences.
  2. Bridge Academia & Industry: Work directly with Prof. Priya Narasimhan (Carnegie Mellon University) and her research team to translate academic innovations into applied systems. Mentor CMU students, collaborate on research projects, and shape the next generation of sports AI researchers.
  3. From Research to Product: Own the path from prototype to production. You'll participate in design reviews, handle real-world deployment challenges, and see your ideas impact actual fan experiences at scale.

CORE REQUIREMENTS.
  • PhD in Computer Vision, Machine Learning, Computer Science, or a closely related field
  • Strong publication track record in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.)
  • Deep expertise in modern computer vision techniques: neural networks, object detection, semantic/instance segmentation, action recognition, optical flow, pose estimation, or related areas
  • Proficiency in ML frameworks (PyTorch, TensorFlow) and modern deep learning practices
  • Strong software engineering fundamentals: Python, Java, AWS, SQL, Redshift, version control, testing, CI/CD
  • Demonstrated ability to implement complex systems end-to-end
  • Background in sports analytics, sports tech, or applied computer vision (industry, research, or both)
  • Genuine enthusiasm for sports and AI
  • Genuine enthusiasm for going beyond book learning, and to have ideas go into large-scale production

HOW TO APPLY
Please submit:
  1. Your CV (with publication list) and research statement.
  2. A cover letter describing your research interests and why you're excited about this opportunity
  3. Links to your top 2-3 publications hat best represent your work

Apply