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Aws Sports Analytics Jobs (NOW HIRING)

AEG

Research Engineer (AI + Sports)

Pittsburgh, PA · On-site

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 ...

DCG Poland

NY · On-site

$90 - $150/hr

Support the design of advanced data and analytics solutions * Collaborate with stakeholders to ... Private medical care * Co‑financing for the sports card * Constant support of dedicated ...

Diverse CG Sp. z o.o. Sp.k.

NY · On-site

$90 - $140/hr

Support the design of advanced data and analytics solutions * Collaborate with stakeholders to ... Private medical care * Co‑financing for the sports card * Constant support of dedicated ...

Lorven Technologies

Data Engineer

$117K - $140K/yr

Our Sports Analytics & Engineering Practice is seeking a seasoned Senior Data Engineer, whose ... Experience working with Cloud data platforms, preferably AWS (Lambda, Step Functions, S3, Glue ...

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Aws Sports Analytics information

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$177.5K

How much do aws sports analytics jobs pay per year?

As of Sep 7, 2026, the average yearly pay for aws sports analytics in the United States is $136,232.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $144,500.00 per year, depending on experience, location, and employer.

What is an AWS Sports Analytics job?

An AWS Sports Analytics job involves leveraging Amazon Web Services (AWS) to analyze sports data for performance insights, strategy optimization, and decision-making. Professionals in this role use cloud-based tools like AWS Glue, Lambda, SageMaker, and Redshift to process and visualize large datasets from games, athletes, and teams. They work with machine learning models, real-time analytics, and data pipelines to improve team performance, fan engagement, and business operations. This role requires expertise in data engineering, statistics, and cloud computing to turn raw sports data into actionable insights.

What are the day-to-day responsibilities of an AWS Sports Analytics professional?

In AWS Sports Analytics positions, you'll typically be responsible for collecting, cleaning, and analyzing large volumes of sports data using cloud-based tools. You may build or maintain machine learning models to predict player performance, optimize team strategies, or enhance fan engagement. Collaboration is frequent, as you'll work closely with data engineers, coaches, and stakeholders to translate data insights into actionable recommendations. The work environment is often fast-paced, requiring adaptability, attention to detail, and continuous learning to keep up with technological advancements and evolving sports analytics needs.

What are the key skills and qualifications needed for an AWS Sports Analytics role?

To excel in AWS Sports Analytics, you need expertise in data analysis, statistics, and a solid understanding of cloud computing, often supported by a degree in data science, computer science, or a related field. Proficiency with AWS services (such as S3, Redshift, and SageMaker), data visualization tools like Tableau or Power BI, and relevant certifications like AWS Certified Data Analytics are highly valuable. Strong communication, problem-solving skills, and the ability to collaborate effectively with cross-functional teams are essential soft skills. These competencies ensure you can deliver actionable sports insights, architect scalable solutions, and support data-driven decision-making in high-performance environments.

Are AWS Sports Analytics jobs still in demand?

AWS Sports Analytics jobs are in demand as sports organizations increasingly adopt cloud-based data analysis and machine learning tools. These roles often require skills in data science, AWS services, and sports data management, with demand driven by the growth of digital sports analytics and real-time data processing.

Is there a career in aws sports analytics?

A career in AWS sports analytics involves using Amazon Web Services tools to analyze sports data, requiring skills in data analysis, cloud computing, and sports metrics. Professionals often work with data visualization, machine learning, and real-time data processing to support team strategies and performance insights.
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Aws Sports Analytics jobs near you
Infographic showing various Aws Sports Analytics job openings in the United States as of August 2026, with employment types broken down into 50% Part Time, and 50% Contract. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $136,232 per year, or $65.5 per hour.

Research Engineer (AI + Sports)

YinzCam Inc.

Pittsburgh, PA • On-site

Full-time

Re-posted 12 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