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Toronto Blue Jays

Data Scientist, Baseball Research

Toronto, ON, M5V 1J1, Canada

Salary: The anticipated base compensation range for this role is $115,000 - $130,000. · Full-time

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Job details

Pay: Salary: The anticipated base compensation range for this role is $115,000 - $130,000.
Job type: Full-time
Posting language: English
Posted: Oct 27, 2026

Original job description

Toronto Blue Jays are seeking a Data Scientist, Baseball Research to help drive innovative, data-informed decision-making across Baseball Operations. Combining advanced quantitative research with a deep understanding of baseball, this role will design predictive models, develop advanced metrics, and explore new data sources and technologies to solve complex baseball questions.

Primary Focus:

Conduct baseball research and contribute to ongoing departmental research
Provide leadership and support to more junior members of the Baseball Research team
Create tools that incorporate data into the decision-making process, as well as learning how decisions are made in all areas of Baseball Operations and working to improve those processes
Challenge current technical processes, explore new data sources that could provide competitive advantages, and propose novel ways to solve data-intensive problems

Responsibilities and Duties:

Design, test, implement and maintain advanced baseball metrics and predictive models to contribute to strategy and decisions across all departments within Baseball Operations. Specific areas of focus could include Pro Scouting, Amateur Scouting, International Scouting, Player Development, Player Projections, or Fundamental Research
Conduct empirical research related to in-game strategy, player evaluation and player procurement whilst understanding how findings would apply to better decision making and increased operational effectiveness.
Offer technical expertise to other members of the Baseball Research Department, providing constructive feedback and guidance
Collaborate with the front office, including other members of the Baseball Research department, coaches, and scouts about research being done. Results of these interactions should help those within the organization better understand, consider, and apply the use of information and data to their decisions
Work with the Baseball Systems team to integrate new information into existing Baseball Operations processes and infrastructure

Experience and Job Requirements:

4-5+ years working in the data science field, building predictive models and communicating results to non-technical users
Passion for baseball and excellent reasoning, problem-solving, creative thinking, and communication skills
Strong interpersonal skills to communicate effectively with a wide range of individuals including members of the front office, scouts, and field staff
Demonstrated ability to successfully design and execute rigorous quantitative research projects
Strong understanding of current baseball research
Proficiency with SQL, R, Python, relational database and/or similar statistical language
Demonstrated ability to use LLMs and generative AI in the research process
Experience with Bayesian modeling, computer vision, biomechanical data, or time-series modeling are all beneficial, but not required
Empathetic approach to work with multicultural populations and a commitment to fairness and equality
Ability to work occasional evening, weekend, and holiday hours as dictated by the baseball calendar

Salary: The anticipated base compensation range for this role is $115,000 - $130,000. Actual base pay offered within this range may differ based on a range of factors, including individual experience, education, skills, and organizational needs.

In addition to your base compensation, you will enjoy discretionary bonus opportunities, vacation entitlements, a comprehensive benefits package, and front‑office perks that reflect the excitement and community of working in baseball.

Position Status: New

WHAT WE OFFER TO YOU

Commitment to our team - we want you to succeed!

Ongoing, hands-on training to help you develop your skills

Excellent employee discount to use towards Blue Jays gear

A unique employment experience working for the only MLB team in Canada

Blue Jays has a strong commitment to diversity, accessibility and inclusion. Everyone who applies for a job will be considered. We encourage individuals from underrepresented groups to apply and join us in shaping the future of our club. Together, we will build a team that reflects the richness of the game and the communities that we represent.

Throughout the recruitment process, we are dedicated to working with candidates who have accessibility needs to ensure they have the necessary support to perform at their best. Questions regarding accessibility throughout the recruitment process can be directed to tbj.careers@bluejays.com.

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More about this job

Responsibilities

The Data Scientist will design, implement, and maintain advanced predictive models and metrics to drive decision-making across Baseball Operations. They will also provide technical leadership to the research team and collaborate with coaches and scouts to integrate data-driven insights into organizational processes.

Requirements

Candidates must have 4-5+ years of experience in data science with a strong background in building predictive models and communicating results to non-technical stakeholders. Proficiency in SQL, R, and Python is required, along with a deep understanding of baseball research and excellent problem-solving skills.

Skills

Data science
Predictive modeling
SQL
R
Python
Baseball research
Quantitative research
Statistical analysis
LLMs
Generative AI
Bayesian modeling
Computer vision
Biomechanical data
Time-series modeling
Problem-solving
Communication

Benefits

Discretionary bonus opportunities
Vacation entitlements
Front-office perks
Employee discount

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Baseball Operations
Predictive Models
Quantitative Research
SQL
R
Python
LLMs
Generative AI
Bayesian Modeling
Computer Vision
Biomechanical Data
Time-series Modeling
Pro Scouting
Amateur Scouting
Player Development
Player Projections
In-game Strategy
Relational Database
Statistical Language
Baseball Research
Data-informed Decision-making
Front Office
Empirical Research
Technical Expertise

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