Boston Red Sox and Fenway Sports Management
Computer Vision Analyst
Boston Red Sox and Fenway Sports Management, Boston, Massachusetts, us, 02298
Computer Vision Analyst
The Boston Red Sox are seeking a Computer Vision Analyst to join our Baseball Sciences group. This role will focus on developing and deploying computer vision methods that transform raw video into actionable data at scale, driving improvements in player evaluation, training environments, and performance analysis. Working within a collaborative research and development team, the Computer Vision Analyst will help advance our ability to extract meaningful signals from the wealth of video available across baseball operations. This is an opportunity to apply advanced quantitative skills to a broad range of problems in baseball sciences, supporting scouting, player development, and sports performance initiatives. Responsibilities:
Develop and refine computer vision models to extract meaningful features from video, generating new datasets that enhance player analysis and performance research. Collaborate with developers, analysts, and stakeholders to ensure computer vision outputs integrate effectively into organizational tools, systems, and workflows. Build pipelines for video processing, feature extraction, and event detection at scale. Partner with Baseball Sciences, Player Development, and other stakeholders to identify opportunities where video-derived data can enhance evaluation and training. Contribute to the broader innovation roadmap of the Baseball Sciences department identifying novel opportunities for computer vision and machine learning applications. Qualifications:
Bachelor's, Master's, or PhD in Computer Vision, Machine Learning, Computer Science, Engineering, Applied Mathematics, or a related quantitative field is preferred. Demonstrated experience developing and deploying computer vision models and algorithms using frameworks such as PyTorch, TensorFlow, Keras, OpenCV, or similar. Proficiency in Python or R, with experience handling large-scale video and image datasets. Experience applying computer vision methods to sports, biomechanics, or human movement data is a plus. Familiarity with database technologies (SQL) and data pipeline development. Background in machine learning model deployment, cloud computing environments, or scalable infrastructure. Experience leveraging AI-assisted analysis tools for identifying and implementing solutions. Knowledge of public baseball analytics research or prior experience working with sports performance data is a plus. Strong critical thinking skills, intellectual curiosity, and ability to communicate findings clearly to both technical and non-technical stakeholders. In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB.
The Boston Red Sox are seeking a Computer Vision Analyst to join our Baseball Sciences group. This role will focus on developing and deploying computer vision methods that transform raw video into actionable data at scale, driving improvements in player evaluation, training environments, and performance analysis. Working within a collaborative research and development team, the Computer Vision Analyst will help advance our ability to extract meaningful signals from the wealth of video available across baseball operations. This is an opportunity to apply advanced quantitative skills to a broad range of problems in baseball sciences, supporting scouting, player development, and sports performance initiatives. Responsibilities:
Develop and refine computer vision models to extract meaningful features from video, generating new datasets that enhance player analysis and performance research. Collaborate with developers, analysts, and stakeholders to ensure computer vision outputs integrate effectively into organizational tools, systems, and workflows. Build pipelines for video processing, feature extraction, and event detection at scale. Partner with Baseball Sciences, Player Development, and other stakeholders to identify opportunities where video-derived data can enhance evaluation and training. Contribute to the broader innovation roadmap of the Baseball Sciences department identifying novel opportunities for computer vision and machine learning applications. Qualifications:
Bachelor's, Master's, or PhD in Computer Vision, Machine Learning, Computer Science, Engineering, Applied Mathematics, or a related quantitative field is preferred. Demonstrated experience developing and deploying computer vision models and algorithms using frameworks such as PyTorch, TensorFlow, Keras, OpenCV, or similar. Proficiency in Python or R, with experience handling large-scale video and image datasets. Experience applying computer vision methods to sports, biomechanics, or human movement data is a plus. Familiarity with database technologies (SQL) and data pipeline development. Background in machine learning model deployment, cloud computing environments, or scalable infrastructure. Experience leveraging AI-assisted analysis tools for identifying and implementing solutions. Knowledge of public baseball analytics research or prior experience working with sports performance data is a plus. Strong critical thinking skills, intellectual curiosity, and ability to communicate findings clearly to both technical and non-technical stakeholders. In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB.