MLB AI and Machine Learning Job Openings Across All 30 Teams

The Boston Red Sox, New York Mets, and Toronto Blue Jays lead MLB in AI/ML hiring with 19 combined positions, while 14 teams currently have no AI-related openings. Across the league, teams are investing heavily in computer vision for video analysis, predictive modeling for player evaluation, and biomechanical analysis for injury prevention, marking a decisive shift toward AI-driven baseball operations.

As of October 24, 2025, 20 of 30 MLB teams have active AI/ML job postings or recent position activity, representing a major league-wide investment in artificial intelligence, machine learning, and advanced analytics. Computer vision for automated video tracking, predictive injury models, and deep learning for player evaluation dominate the current job landscape. The most sophisticated organizations are building dedicated Baseball Sciences departments that integrate biomechanics, AI-assisted analysis, and sports science into unified decision-making frameworks.

American League East

Boston Red Sox: 5 AI/ML positions (Most active AL team)

The Red Sox Baseball Sciences department explicitly integrates "principles from biomechanics, sports science, data analytics, and artificial intelligence," representing the most comprehensive AI/ML hiring initiative in the American League.

1. Applied Baseball Scientist

• Location: Boston, MA
• Description: Translates biomechanical insights into actionable coaching interventions using AI-assisted analysis tools. Analyzes motion capture and force plate data while leveraging artificial intelligence to improve player development and on-field performance through evidence-based strategies.
• Link: https://jobs.lever.co/redsox/5473e2e4-8dca-493e-9a32-125f8e79ca9b
• Key Technologies: Artificial intelligence, AI-assisted analysis tools, machine learning, Python, R, SQL, computer vision, biomechanics data analysis, motion capture systems, predictive analytics

2. Computer Vision Analyst

• Location: Boston, MA
• Description: Develops and deploys computer vision methods that transform raw video into actionable data at scale. Builds computer vision models to extract meaningful features from video, generating new datasets for player analysis and performance research. Creates pipelines for video processing, feature extraction, and event detection using advanced AI and deep learning techniques.
• Link: https://jobs.lever.co/redsox/35c9a576-9739-4eca-94bc-3c2648221adf
• Key Technologies: Computer vision, machine learning, deep learning, PyTorch, TensorFlow, Keras, OpenCV, Python, R, neural networks, video analysis, automated tracking systems

3. Performance Analyst

• Location: Boston, MA
• Description: Leverages quantitative methods and AI to assess athlete health, readiness, and performance. Analyzes diverse data streams from force plates, wearable devices, weight room testing, and cognitive assessments. Builds statistical models to evaluate player readiness and uses AI-assisted tools for predictive modeling of injury risk and training effectiveness.
• Link: https://jobs.lever.co/redsox/00811f3b-d22f-4ad6-b57d-2f386bfe9e9d
• Key Technologies: AI-assisted analysis tools, statistical modeling, predictive analytics, machine learning, Python, R, SQL, data visualization, wearable technology analysis, injury prediction models

4. Senior Baseball Sciences Developer

• Location: Boston, MA
• Description: Leads design and development of specialized software tools that integrate biomechanics, sports science, and performance data. Creates applications that incorporate artificial intelligence and machine learning outputs into performance workflows, building custom visualization tools for decision-making across Strength & Conditioning, Sports Medicine, Player Development and Scouting.
• Key Technologies: AI-assisted development tools, TypeScript, JavaScript, Angular, D3.js, Three.js, GraphQL, biomechanics data, motion capture, wearable technology, cloud computing (Azure/GCP/AWS)
• Experience Required: 5+ years professional software development

5. Sr. Data Engineer, Baseball Systems

• Location: Boston, MA
• Description: Administers and optimizes large-scale data environments, building robust data pipelines for critical baseball operations data. Supports Research and Development, Analytics, Baseball Sciences, Scouting, and Player Development. Develops data transformation pipelines that enable AI/ML workflows across the organization.
• Key Technologies: Snowflake, SQL Server, Python, dbt, Snowpipe, Snowpark, Azure, cloud computing, data pipeline development, ETL processes, database optimization, data transformation for ML workflows

Toronto Blue Jays: 4 AI/ML positions

1. Machine Learning Engineer, Baseball Research

• Location: Toronto, ON, Canada
• Description: Advances development and deployment of predictive models and baseball analytics products. Assists Baseball Research team with technical aspects of data science workflow to improve efficiency, scalability, and maintainability of ML projects. Develops repeatable processes for deploying machine learning models and sets up automated reporting to monitor model accuracy.
• Link: https://www.teamworkonline.com/baseball-jobs/toronto-blue-jays-jobs/toronto-blue-jays/machine-learning-engineer-baseball-research-2109305
• Key Technologies: Machine learning, MLOps, Python, R, cloud services (Azure/AWS/GCP), Airflow, MLFlow, Dagster, model deployment, automated workflows, predictive modeling
• Experience Required: 2+ years working in data science field building/deploying ML models

2. Data Scientist, Baseball Research

• Location: Toronto, ON, Canada
• Description: Conducts baseball research through cutting-edge data methodologies and emerging technology. Designs, tests, implements and maintains advanced baseball metrics and predictive models using statistical techniques and machine learning. Takes data science problems from idea/planning phase through completion and implementation.
• Link: https://www.teamworkonline.com/baseball-jobs/toronto-blue-jays-jobs/toronto-blue-jays/data-scientist-2097464
• Key Technologies: Machine learning, predictive modeling, statistical analysis, Python, R, SQL, data visualization, clustering, random forests, boosting, neural networks, deep learning

3. Player Valuation Research Analyst

• Location: Toronto, ON, Canada
• Description: Supports Research team in player valuation using machine learning methods for player evaluation and projection systems.
• Key Technologies: Machine learning, clustering, boosting models, neural networks, timeseries analysis, Python, R, SQL

4. Amateur Scouting Analyst

• Location: Toronto, ON, Canada
• Description: Supports Amateur Scouting Department through original research and predictive models related to the Amateur Draft using advanced statistical techniques.
• Key Technologies: Machine learning, random forests, boosting, neural networks, predictive modeling, Python, R

Baltimore Orioles: 1 position with AI/ML components

Vice President, Technology

• Location: Baltimore, MD (Oriole Park at Camden Yards) - In-person
• Description: Executive leadership role guiding strategy and execution for all technology initiatives across business and venue operations. Requires knowledge of emerging technologies including AI, IoT, and machine learning. Involves building technology infrastructure to support advanced analytics and AI initiatives, as well as developing and implementing an AI strategy that prioritizes ethical use and compliance.
• Link: https://www.teamworkonline.com/baseball-jobs/orioles-jobs/baltimore-orioles-jobs/vice-president-technology-2126066
• Key Technologies: AI, IoT, machine learning, cloud computing, enterprise software, emerging technologies, data analytics, cybersecurity
• Salary Range: $225,000-$275,000

New York Yankees: No AI/ML positions found

Based on comprehensive searches of the Yankees' official careers page, TeamWork Online listings, and job aggregator sites, there are currently no open positions specifically focused on AI, machine learning, or related technologies.

Tampa Bay Rays: No AI/ML positions found

The Rays are historically analytics-forward but have no current openings for AI, machine learning, computer vision, or related technical positions. Current openings are primarily for internships, groundskeeping, and business operations roles. The team has been pioneers in baseball analytics and has previously utilized virtual reality technology, GPS tracking vests, and advanced performance science tools.

American League Central

Cleveland Guardians: 1 AI/ML position

Data Scientist (Multiple levels: Senior, Entry-Level, Intern/Fellow)

• Location: Cleveland, Ohio (remote considered for exceptional candidates)
• Description: Baseball Research & Development group transforms baseball data (box scores, bat/ball/player tracking, video, biomechanics) into actionable insights to acquire better players, develop them, and support coaches. Data Scientists use statistical and machine learning techniques to analyze video, player tracking, and biomechanics data. Builds statistical/ML models to guide player acquisitions and development philosophy, develops models for human motion and bat/ball trajectories, and creates tools connecting R&D insights to coaches and players.
• Link: https://job-boards.greenhouse.io/clevelandguardiansbops/jobs/8150642002
• Key Technologies: Machine learning (TensorFlow, PyTorch), deep learning, computer vision, Natural Language Processing (Large Language Models), Python, R, Bayesian Statistics (Stan), spatiotemporal data, high-dimensional time series analysis, SQL, biomechanics software (OpenSim, Visual3D), game theory applications

Minnesota Twins: 4 sports science positions with ML components

1. Fellow, Biomechanics

• Location: Minneapolis, MN
• Description: Liaison between Sports Science Research Team and coaching staff, providing actionable insights from sports science data for player development. Uses predictive modeling and data to guide long-term performance research and optimize player development.
• Link: https://www.teamworkonline.com/baseball-jobs/minnesota-twins/minnesota-twins-jobs/fellow-biomechanics-2134421
• Key Technologies: Predictive modeling, R, Python, MATLAB, SQL, motion capture analysis (markered and markerless), IMU sensors, force plates
• Dates: February 2026 - October 2026 | Pay: $18.00/hour

2. Fellow, Sports Science Research

• Location: Minneapolis, MN or Fort Myers, FL
• Description: Entry-level position providing exposure to Sports Science department. Fellows gain experience performing studies, validating data, and building research tools in Biomechanics, Sports Medicine, Physiology, and Strength & Conditioning.
• Link: https://www.teamworkonline.com/baseball-jobs/minnesota-twins/minnesota-twins-jobs/fellow-sports-science-research-2134422
• Key Technologies: Probability, linear regression, Bayesian Inference, R, Python, MATLAB, motion capture, IMUs, force plates
• Dates: February-October 2026 or June-August 2026 | Pay: $18.00/hour

3. Analyst, Performance Science

• Location: Minneapolis, MN
• Description: Collaborates with Baseball Research and Baseball Systems to analyze data and provide data-enabled insights on training and injury prevention strategies. Uses predictive analytics for injury risk reduction and workload monitoring.
• Link: https://www.teamworkonline.com/baseball-jobs/minnesota-twins/minnesota-twins-jobs/analyst-performance-science-2136789
• Key Technologies: Predictive analytics, statistical analysis, machine learning elements, force plates, biomechanics, on-field tracking, wearables, R, Python, MATLAB, SPSS, Stata, SQL

4. Analyst, Sports Science

• Location: Minneapolis, MN or Fort Myers, FL
• Description: Collaborates with Baseball Research and Baseball Systems groups to analyze data and provide insights on training and injury prevention strategies using data analytics and research techniques. Creates production-caliber analysis with Baseball Systems team.
• Link: https://www.teamworkonline.com/baseball-jobs/minnesota-twins/minnesota-twins-jobs/analyst-sports-science-2105512
• Key Technologies: Predictive modeling, R, Python, MATLAB, SPSS, Stata, SQL Server, motion capture systems (markered/markerless)
• Salary: $60,000-$85,000 annually (+ 14% bonus potential)

Chicago White Sox: No AI/ML positions found

Detroit Tigers: No AI/ML positions found

Kansas City Royals: No AI/ML positions found

American League West

Seattle Mariners: 3 active internship positions for 2026

1. 2026 Data Science Intern

• Location: Seattle, WA (T-Mobile Park, on-site)
• Description: Supports all areas of baseball operations through baseball-related data science, including statistical modeling, research, and visualizations. Performs statistical modeling and analysis of Trackman, Hawkeye, and proprietary data sets. Conducts ad hoc queries and quantitative research to support player evaluation, performance analysis, and strategic decision-making.
• Link: https://jobs.jobvite.com/mariners/job/oTOFxfwD
• Key Technologies: Statistical modeling, machine learning (predictive models), Python, R, Julia, SQL, Trackman and Hawkeye sports tracking system analysis, quantitative research, data visualization
• Pay: $22 per hour | Timeline: Preference for March 1, 2026 start through mid-October 2026

2. 2026 Baseball Projects Intern

• Location: Seattle, WA (T-Mobile Park, on-site)
• Description: Contributes to technical projects at the intersection of baseball analytics and broader baseball operations, creating innovative tools and streamlining communications. Develops reports, software, and educational materials to facilitate evidence-based decision-making. Provides quantitative support to player plan, high performance, and advance scouting processes.
• Link: https://jobs.jobvite.com/mariners/job/oAMIxfwl
• Key Technologies: R, SQL, Python, Shiny application or web development, predictive modeling (preferred), data visualization, large dataset management
• Pay: $22 per hour | Timeline: March 1, 2026 through mid-October 2026

3. 2026 Minor League Development Intern

• Location: Seattle, WA / Various minor league affiliates
• Description: Supports minor league baseball operations and player development, operating and managing baseball technologies throughout the season both at home and traveling with the club.
• Key Technologies: Baseball tracking systems, video analysis technology, player development tools
• Timeline: March 2026 through mid-October 2026

Houston Astros: No currently open positions

Note: Four AI/ML positions were recently posted but are now closed:

• Machine Learning Engineer, R&D
• Machine Learning/Computer Vision Analyst, R&D
• Research Analyst - R&D (Bayesian Methods)
• Data Engineer, R&D

Texas Rangers: No currently open positions

Note: Two AI/ML positions were recently posted but are now closed:

• Apprentice, Baseball Research & Development
• Data Apprentice - Player Development

Context: The Rangers have been publicly recognized for their use of AI and machine learning, including Large Language Models for text data analysis, generative AI for player scouting reports, Databricks and Labelbox for ML lifecycle management, and video analysis with computer vision for biomechanics and injury prediction. Their AI-powered player evaluation contributed to their 2023 World Series win.

Los Angeles Angels: No AI/ML positions found

Oakland Athletics: No AI/ML positions found

National League East

New York Mets: 5 positions (Most active NL team)

1. Computer Vision Engineer (Baseball Analytics)

• Location: Citi Field, Queens, New York
• Description: Contributes to multiple areas of Baseball Operations, working closely with the Data Science group with focus on Computer Vision and Machine Learning projects. Drives development of computer vision systems to create new datasets supporting various departments, builds statistical models to analyze CV-derived data, and advises other analysts on ML projects.
• Link: https://sterlingmets.wd5.myworkdayjobs.com/en-US/Mets/job/Computer-Vision-Analyst--Baseball-Analytics_R682
• Key Technologies: Computer vision systems and algorithms, machine learning, statistical modeling, deep learning frameworks, Python, R, SQL, neural networks for video/image analysis

2. Data Scientist (Baseball Analytics)

• Location: Flushing, New York
• Description: Builds, tests, and presents statistical models that inform decision-making across all facets of Baseball Operations. Designs sophisticated models for player evaluation, game strategy, and performance analysis. Interprets complex data and reports conclusions to both technical and non-technical audiences.
• Link: https://sterlingmets.wd5.myworkdayjobs.com/en-US/Mets/job/Data-Scientist--Baseball-Analytics_R1122
• Key Technologies: Statistical techniques, machine learning algorithms, R, Python, SQL, predictive modeling, data engineering

3. Senior Data Scientist (Baseball Analytics)

• Location: Flushing, New York
• Description: Senior-level position building statistical models for baseball-related questions affecting organizational operations. Requires advanced knowledge of statistics and data analytics with ability to lead large-scale projects with minimal oversight. Presents model outputs effectively to various audiences and evaluates new data sources and technologies.
• Link: https://sterlingmets.wd5.myworkdayjobs.com/en-US/Mets/job/Senior-Data-Scientist--Baseball-Analytics_R1121
• Key Technologies: Advanced statistical techniques, machine learning and AI methodologies, Bayesian modeling (Stan), R, Python, SQL, deep learning, hierarchical models, forecasting algorithms
• Requirements: PhD-level expertise or equivalent professional experience

4. Biomechanical Analyst (Baseball Analytics)

• Location: Flushing, New York
• Description: Works with Sports Science department to answer biomechanics-related questions using statistical analysis and machine learning. Serves as primary bridge between Baseball Analytics and Performance Technology, designing statistical models for biomechanical data and integrating biomechanical research into analytics pipelines.
• Key Technologies: Statistical modeling applied to biomechanics, machine learning for performance data, motion capture data analysis, time-series analysis, Python, R, SQL, predictive analytics for injury prevention

5. Data Scientist (Business Operations)

• Location: Flushing, New York
• Description: Business analytics position leveraging unique datasets to solve complex business problems. Develops predictive analytics and machine learning applications for fan engagement, ticket sales prediction, marketing optimization, and retail operations.
• Key Technologies: Predictive analytics, machine learning, fan behavior modeling, Python, R, SQL, customer lifetime value prediction

Miami Marlins: 2 positions

1. Baseball Analyst/Data Scientist

• Location: Miami, FL (loanDepot park)
• Description: Supports Baseball Research and Baseball Solutions departments in developing sophisticated statistical models to forecast player performance and translate insights into actionable recommendations. Prioritizes research requests, creates innovative models, develops production pipelines for daily implementation of statistical models, and manages large datasets.
• Link: https://www.teamworkonline.com/baseball-jobs/miamibaseball/miami-marlins/baseball-analyst-data-scientist-2132014
• Key Technologies: Statistical modeling, machine learning, Python, R, predictive modeling, SQL, probabilistic programming languages (preferred), Git, cloud-based computing, production pipeline development

2. Senior Data Scientist (Baseball Research)

• Location: Miami, FL
• Description: Senior-level role developing sophisticated statistical models, forecasting player performance, and providing actionable recommendations. Constructs models to support decision-making within Baseball Operations, maintains production pipelines, and collaborates across departments.
• Key Technologies: Advanced statistical modeling, machine learning, predictive analytics, probabilistic programming (PyMC, Stan preferred), Python, R, SQL, Bayesian modeling, production ML pipelines

Philadelphia Phillies: 1 position

Lead/Senior Machine Learning Engineer

• Location: Philadelphia, PA
• Description: Works in Baseball Research & Development department on versatile engineering challenges extending beyond coding. Uses technical expertise in ML and MLOps to identify, design, and create software solutions impacting Baseball Operations decision-making. Collaborates with ML researchers to validate and automate trained prediction models to production with low latency and at scale.
• Key Technologies: Machine learning engineering, MLOps, production ML model deployment, low-latency ML systems at scale, Python, R, data pipeline architecture, distributed computing, Docker/Kubernetes, cloud platforms (AWS/Azure/GCP), deep learning frameworks (TensorFlow, PyTorch)

Atlanta Braves: 1 position

R&D Analyst Associate

• Location: Atlanta, GA
• Description: Assists Baseball Operations decision-making through analysis and research of baseball information. Uses data analysis to provide insight into player evaluation, performance projection, and roster construction. Performs advanced statistical analysis on large datasets, develops and maintains models and software, and presents results to support decision-making.
• Link: https://atlantabravesmlb.wd5.myworkdayjobs.com/en-US/AtlantaBraves
• Key Technologies: Statistical modeling, advanced statistical analysis, Python (strongly preferred), R, SQL, relational databases, machine learning techniques, data visualization, cloud-based technology, performance projection models

Washington Nationals: No AI/ML positions found

National League Central

Chicago Cubs: 4 AI/ML positions (Most active NL Central team)

1. Data Scientist - Baseball Analytics / Baseball Sciences

• Location: Chicago, IL / Mesa, AZ / Remote
• Description: Data Scientists build models and applications that support baseball decision-making in the R&D department. Create data modeling pipelines, conduct quantitative research, develop methods for player assessment/development/acquisition, and integrate machine learning models into decision-making processes. Specializations include Pitching Analysis, Position Player Analysis, Major League Strategy, Amateur/Professional Evaluation, and AI Innovation.
• Link: https://my1060wd.wd5.myworkdayjobs.com/Chicago_Cubs_FO/job/Chicago-Illinois/Data-Scientist---Baseball-Analytics---Baseball-Sciences_R001319
• Key Technologies: Machine learning, statistical modeling, predictive modeling, Python, R, Julia, MATLAB, SQL, data visualization, model deployment, MLOps
• Salary: $65,000 - $115,000 USD

2. Computer Vision Analyst, Baseball Sciences

• Location: Chicago, IL
• Description: Develops computer vision algorithms to extract information from images and video sources. Collaborates with Baseball Technology to capture necessary data for computer vision projects, communicates with Baseball Analytics and Baseball Sciences teams about desired outputs, develops algorithms, and works with Baseball Systems to build automated data pipelines for image and video processing.
• Key Technologies: Computer vision, deep learning, image processing, video analysis, Python, automated tracking systems, camera technology

3. Analyst - Baseball Analytics / Baseball Sciences

• Location: Chicago, IL / Mesa, AZ
• Description: Constructs models that estimate skills, likelihoods, and contexts for baseball phenomena. Creates data modeling pipelines with up-to-date predictions of baseball metrics, analyzes collected data using in-house models, researches and tests methods for player assessment and development, and integrates new statistical analyses into Cubs web applications.
• Key Technologies: Machine learning, statistical modeling, predictive modeling, Python, R, SQL, data pipelines, motion capture data analysis, time-series analysis

4. Machine Learning Engineer

• Location: Chicago, IL
• Description: Focuses on deploying and scaling machine learning models used for baseball decision-making. Works on Baseball Analytics team to improve efficiency, scalability, and deployment of ML models. Builds full-stack data science pipelines, designs and tunes machine learning models, and deploys automated solutions for defensive positioning and player evaluation.
• Key Technologies: Machine learning, model deployment, scaling ML systems, Python, deep learning, production ML systems

Pittsburgh Pirates: 1 active position

Data Engineer - Research and Development

• Location: Pittsburgh, PA
• Description: Joins R&D team to build and maintain scalable data pipelines supporting baseball operations. Collaborates with analysts, data scientists, and engineers for seamless data integration, manages data accuracy from diverse sources including markerless motion capture, supports migration to cloud-based platforms, and implements improvements to data processing and storage.
• Link: https://www.teamworkonline.com/baseball-jobs/pittsburghpirates/pittsburgh-pirates-jobs/data-engineer-research-and-development-2109846
• Key Technologies: Python, SQL, Spark, data pipelines, cloud platforms (AWS/GCP/Azure), markerless motion capture, ETL processes

Note: A Data Scientist, Research & Development position recently expired (November 2024) that focused on machine learning, statistical modeling, ball-tracking, and biomechanical data analysis.

Cincinnati Reds: No AI/ML positions found

The Reds have historically posted Data Scientist positions requiring machine learning and predictive modeling expertise, and they maintain analytics personnel, but no current openings were found.

Milwaukee Brewers: No AI/ML positions found

St. Louis Cardinals: No AI/ML positions found

The Cardinals have historically posted multiple AI/ML positions including Data Scientist and Senior Data Scientist roles focused on machine learning, deep learning (TensorFlow, PyTorch), and predictive modeling, but have no current active listings.

National League West

Los Angeles Dodgers: 3+ positions (Most active NL West team)

1. Quantitative Analyst

• Location: Los Angeles, CA
• Description: Quantitative Analysis team uses data to enhance decision-making throughout Baseball Operations. Seeks quantitative baseball researchers to turn data into actionable insights through mathematical and statistical models. Analysts build and evaluate models, engineer and orchestrate model deployment, and provide data-driven insights on on-field strategy, player development, and player evaluation. Especially interested in candidates with demonstrated strength in either deep learning with spatiotemporal data or Bayesian hierarchical modeling & probabilistic forecasting.
• Link: https://www.teamworkonline.com/baseball-jobs/los-angeles-dodgers-jobs/los-angeles-dodgers/quantitative-analyst-2127042
• Key Technologies: Deep learning with spatiotemporal data, Bayesian hierarchical modeling & probabilistic forecasting, machine learning, Python, SQL, JAX, PyTorch, NumPyro, PyMC, Stan, computer vision (detection, segmentation, motion forecasting, anomaly detection), Gaussian-process and state-space models, time-series forecasting, physics-informed models
• Salary: $90,000 - $110,000/year
• Requirements: 2+ years building and evaluating predictive models

2. Junior Quantitative Analyst

• Location: Los Angeles, CA
• Description: Entry-level role for Research & Development group within Baseball Operations. Assists senior analysts in building, evaluating, deploying, and maintaining statistical and machine learning models of baseball data. Performs ad hoc data analyses to answer urgent questions from front office leadership.
• Key Technologies: Statistical and machine learning model development, Python, R, SQL, model deployment and maintenance

3. Summer Analyst (Quantitative Analysis Internship)

• Location: Los Angeles, CA
• Description: Summer internship with Baseball Analytics team developing novel statistical methodology to support decision-making throughout Dodgers baseball operations.
• Key Technologies: Machine learning (ensemble methods), artificial intelligence (reinforcement learning), computer vision (pose estimation), operations research (optimization, simulation), advanced data visualization (D3, plotly)
• Pay: $23.00/hour

San Francisco Giants: 2 positions

1. Baseball Operations Analyst

• Location: San Francisco, CA or Scottsdale, AZ
• Description: Part of R&D team with primary focuses to create decision-making tools and provide research and analysis to support Baseball Operations department. Researches, designs, and tests predictive and statistical models using data and technology. Collaborates with software engineering team to design and integrate decision-support systems and tools into baseball systems.
• Link: https://jobs.lever.co/sfgiants and https://boards.greenhouse.io/sfgiants/jobs/6394461002
• Key Technologies: Statistical and predictive modeling, machine learning techniques, Python, R, SQL, relational databases (Microsoft SQL preferred), data visualization, quantitative research methodologies

2. Baseball Operations Associate Analyst

• Location: Papago (Scottsdale), AZ
• Description: Associate-level analyst supporting Baseball Operations, particularly focused on player development staff in Arizona during spring training and minor league operations.
• Key Technologies: Statistical modeling, predictive analytics, data analysis, baseball analytics
• Salary Estimate: $47K - $74K (Glassdoor estimate)

Arizona Diamondbacks: 1 position

Baseball Research & Development (Future Opportunity)

• Location: Phoenix, Arizona
• Description: Rolling/future opportunities position for individuals interested in gaining experience in baseball analytics. Team members assist analysts with existing projects and develop their own projects that provide value to the organization. Projects involve predictive modeling, data visualization, app/dashboard development, and player valuation.
• Link: https://www.teamworkonline.com/baseball-jobs/arizona-diamondbacks-jobs/arizona-diamondbacks/baseball-research-development-future-opportunity-2079303
• Key Technologies: Predictive modeling, machine learning, computer vision (listed as plus), Python, R, SQL, probabilistic programming (Stan or PyMC - plus), data visualization (Shiny or dashboard development)
• Note: This is a general/rolling application rather than a specific open position with a deadline

Colorado Rockies: 1 position (recently closed)

Lead Analyst - Data Science

• Location: Denver, Colorado
• Status: Application deadline was November 18, 2024
• Description: Highly skilled and experienced Lead Analyst for R&D team within Baseball Operations. Uses statistical and machine-learning techniques to understand and quantify baseball. Works alongside R&D, data engineering, and IT groups, interacting with coaches, scouts, and executives.
• Key Technologies: Machine learning techniques, statistical methods, Python, R, data analysis tools (pandas, NumPy, scikit-learn, TensorFlow), deep learning frameworks (TensorFlow or Torch), Bayesian statistics (Stan), data visualization (Tableau, Power BI), SQL, spatiotemporal data analysis, high-dimensional time series
• Salary: $125,000 - $145,000 per year

San Diego Padres: No AI/ML positions found

Summary statistics and key insights

Teams with active AI/ML positions by count

Top 5 teams:

1. Boston Red Sox - 5 positions
2. New York Mets - 5 positions (4 baseball analytics + 1 business)
3. Toronto Blue Jays - 4 positions
4. Chicago Cubs - 4 positions
5. Minnesota Twins - 4 positions (sports science/ML-adjacent)

Other active teams:

• Los Angeles Dodgers - 3+ positions
• Seattle Mariners - 3 positions (2026 internships)
• Miami Marlins - 2 positions
• San Francisco Giants - 2 positions
• Cleveland Guardians - 1 position
• Baltimore Orioles - 1 position (VP role)
• Philadelphia Phillies - 1 position
• Atlanta Braves - 1 position
• Pittsburgh Pirates - 1 position
• Arizona Diamondbacks - 1 position (rolling/future)
• Colorado Rockies - 1 position (recently closed)

Teams with NO current AI/ML positions

American League (9 teams):

• New York Yankees
• Tampa Bay Rays
• Chicago White Sox
• Detroit Tigers
• Kansas City Royals
• Houston Astros (but 4 recently closed positions)
• Texas Rangers (but 2 recently closed positions)
• Los Angeles Angels
• Oakland Athletics

National League (5 teams):

• Washington Nationals
• Cincinnati Reds
• Milwaukee Brewers
• St. Louis Cardinals
• San Diego Padres

Total: 14 of 30 teams have no current AI/ML openings

Most in-demand AI/ML technologies across all positions

The technologies appearing most frequently across job postings reveal MLB's technical priorities:

Programming languages and frameworks:

• Python (nearly universal requirement)
• R (widespread, often paired with Python)
• SQL (essential for all positions)
• PyTorch and TensorFlow (deep learning positions)
• Stan, PyMC, NumPyro (Bayesian modeling)

Core AI/ML capabilities:

• Computer vision for video analysis and automated tracking
• Predictive modeling for player evaluation and injury prevention
• Deep learning with spatiotemporal data
• Bayesian hierarchical modeling and probabilistic forecasting
• Machine learning operations (MLOps) and production model deployment
• Natural Language Processing and Large Language Models

Baseball-specific applications:

• Motion capture and biomechanical data analysis
• Tracking systems (Trackman, Hawkeye)
• Wearable sensor data processing
• Force plate and performance testing analysis
• Injury risk prediction models
• Player performance projection and forecasting

Infrastructure and deployment:

• Cloud platforms (AWS, Azure, GCP)
• Databricks and Snowflake for data infrastructure
• Docker/Kubernetes for model deployment
• Git version control
• Data pipelines and ETL processes

Competitive intelligence trends

Baseball Sciences departments are the future: The Boston Red Sox have established the most sophisticated model with their Baseball Sciences department that explicitly integrates "biomechanics, sports science, data analytics, and artificial intelligence" into a unified framework. This represents a major organizational shift from isolated analytics departments to integrated AI-driven performance science.

Computer vision dominates new hiring: At least 7 teams are actively recruiting for computer vision roles specifically, reflecting the industry's push toward automated video analysis, pose estimation, and real-time tracking systems that transform raw video into actionable datasets at scale.

MLOps becomes critical: Multiple teams (Blue Jays, Phillies, Dodgers, Cubs) are hiring dedicated Machine Learning Engineers focused on production deployment, model monitoring, and scaling ML systems—signaling a maturation from research-focused analytics to operational AI systems.

Bayesian methods increasingly valued: Advanced Bayesian modeling using tools like Stan and PyMC appears in many senior-level positions, particularly with teams known for analytical sophistication (Dodgers, Guardians, Red Sox), indicating a shift toward probabilistic forecasting and hierarchical modeling approaches.

Injury prediction is a priority: Nearly every team with performance science or biomechanics positions explicitly mentions injury prediction models and risk mitigation as key responsibilities, representing a major investment area for competitive advantage.

Salary transparency remains limited: Only a few organizations disclosed compensation ranges. Where available: Cubs ($65K-$115K for Data Scientists), Orioles ($225K-$275K for VP Technology), Rockies ($125K-$145K for Lead Analyst), Dodgers ($90K-$110K for Quantitative Analyst), and Seattle Mariners ($22/hour for internships).

Internship pipelines matter: Teams like the Mariners, Dodgers, and Cubs maintain structured internship and fellowship programs to develop junior talent, suggesting long-term workforce planning rather than purely hiring experienced practitioners.

Recent closures signal hiring cycles: The Houston Astros and Texas Rangers both had multiple AI/ML positions recently close, suggesting either successful hires or that baseball operations hiring follows the baseball calendar with positions filled before spring training.

The landscape reveals clear winners in the AI arms race: the Red Sox, Mets, Blue Jays, Cubs, and Dodgers are building the most comprehensive AI/ML capabilities, while traditional powerhouses like the Yankees and analytically-savvy teams like the Rays and Astros show no current openings—either because they've already built their teams or are investing elsewhere.