Data Scientist

Maple Leaf Sports & Entertainment Ltd.; Toronto; Hybrid; CAD 105,000 - 115,000; Full time

Job summary

Maple Leaf Sports & Entertainment Ltd. is seeking a skilled analytics scientist to design, implement, and validate predictive models for player evaluation and team performance.

You will work with spatio-temporal data to generate actionable insights for front-office leaders, coaches, and scouts. You will partner with data engineers to build scalable features, production workflows, and leverage advanced ML methods such as Bayesian inference, neural networks, and spatial modeling to inform

Qualifications

• Master’s or Ph.D. in Statistics, Data Science, CS, Applied Math, OR, or equivalent practical quantitative research experience.
• Deep statistical learning knowledge and hands-on ML techniques (GBDTs, hierarchical/mixed-effects, neural nets, spatio-temporal).
• Proficiency in Python and/or R with libraries like scikit-learn, PyTorch, XGBoost, tidyverse, PyMC/Stan.
• Strong SQL skills for large-scale data extraction/aggregation.
• Experience with clean code, Git, unit tests, and reproducible workflows.

Responsibilities

• Design, build, evaluate, and maintain predictive ML models for player evaluation and performance optimization.
• Extract insights from spatio-temporal tracking data to drive player evaluation.
• Conduct exploratory research using Bayesian inference, spatial modeling, survival analysis, or deep learning.
• Audit, backtest, and refine models to maintain accuracy amid changing game rules/economics.
• Collaborate with data engineering to build scalable features and production pipelines.
• Translate model outputs into visualizations and executive briefs for decision-makers.

Skills

Predictive modeling

Statistics

Machine learning

Python

R

SQL

Data visualization

Education

Master’s or Ph.D. in a quantitative field

Tools

scikit-learn

PyTorch

XGBoost

tidyverse

PyMC/Stan

Git

Docker

AWS

GCP

Job description

**Powered by Passion. United by Purpose. Build for Impact.**At Maple Leaf Sports & Entertainment Partnership (MLSE), we exist to deliver the ultimate fan experience by lifting trophies, spirits, and communities – united as one.We're more than a workplace. We are a team of passionate people, boldly building the future of sport and entertainment, together. We believe in the power of play, the strength of collaboration, and the energy that comes from showing up with purpose.From the ice to the pitch, the hardwood to the digital arena, we’re proud to be the driving force behind the Toronto Maple Leafs (NHL), the Toronto Raptors (NBA), Toronto FC (MLS), Toronto Argonauts (CFL) and development teams with the Toronto Marlies (AHL), Raptors 905 (NBA G League), Toronto FC II (MLS NEXT Pro League) and Raptors Uprising Gaming Club, the Toronto Raptors Esports franchise in the NBA 2K League.We bring these teams – and world-class entertainment – to life at our iconic venues, including Scotiabank Arena, BMO Field, Coca-Cola Coliseum, Ford Performance Centre, BMO Training Ground, and OVO Athletic Centre. Off the field, we serve up elevated dining at e11even, Real Sports, and our signature club spaces like Hot Stove Club, ScotiaClub, and Platinum Club.Through MLSE Foundation and MLSE LaunchPad, we use the power of sport to help youth facing barriers reach their full potential. Since 2009, we’ve invested more than $45 million into Ontario communities -- and we’re just getting started.This is what it means to be One MLSE: a culture where everyone plays a role, everyone belongs, and everyone contributes to something bigger than themselves.So, if you're ready to play with purpose, grow with passion, and win as one, we’d love to have you on our team.*\\*\\* We know that great candidates come from a variety of backgrounds and experiences. Even if you do not meet every qualification listed, we encourage you to apply. Your unique perspective, transferable skills, and lived experience may be exactly what we’re looking for. \\*\\****Job Description**Responsibilities* Design, build, evaluate, and maintain predictive statistical and machine learning models for player evaluation, projectable skill growth, player acquisition, tactical simulation, and performance optimization.* Extract actionable insights from spatio-temporal tracking data to drive quantitative player evaluation.* Conduct rigorous exploratory research using advanced quantitative techniques (e.g. Bayesian inference, spatial modeling, survival analysis, or deep learning) to uncover unexploited market inefficiencies.* Systematically audit, backtest, and refine existing internal predictive models to ensure high accuracy and adaptability through changes in game rules or industry economics.* Partner closely with data engineering teams to design scalable features, automated data pipelines, and production workflows for seamless model deployment.* Translate complex probabilistic outputs and model predictions into intuitive visualizations, executive briefs, and actionable insights for front-office leaders, coaches, and scouts.Qualifications* Master’s or Ph.D. in Statistics, Data Science, Computer Science, Applied Mathematics, Operations Research, or equivalent practical quantitative research experience.* Deep statistical learning knowledge and hands-on experience applying machine learning techniques, such as gradient-boosted decision trees, hierarchical/mixed-effects models, neural networks, or spatio-temporal modeling.* Advanced programming proficiency in Python and/or R for numerical computing, data manipulation, and model development (using libraries such as scikit-learn, PyTorch, XGBoost, tidyverse, or PyMC/Stan).* Strong command of SQL for extracting, aggregating, and joining large-scale relational datasets.* Practical experience with software development best practices, including clean code principles, version control (Git), unit testing, and reproducible research workflows.Nice-to-haves:* Experience with stochastic simulation methods (e.g., Monte Carlo) or reinforcement learning for game strategy optimization and decision modeling under uncertainty.* A portfolio of public sports analytics research, open-source sports data science projects, or competition entries evaluating athlete performance or tactical dynamics.* Familiarity with modern MLOps workflows, containerization (Docker), and cloud infrastructure (AWS or GCP) for scaling predictive models.**Job Posting Compensation Range/Rate:**$105,000 - $115,000We’re glad you’re here. Once you apply, we’ll follow up by email, and you can track everything in your **Candidate Portal**. Want instant updates? **Opt-in for SMS notifications** to stay in the loop.At MLSE, we are committed to building an equitable, diverse and inclusive organization. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. MLSE will provide reasonable accommodation for qualified individuals with disabilities in the job application process. If you have difficulty using our online application system and you need an accommodation due to a disability, please email [e-mail]. This email is only for accommodation requests. Resumes sent to this email address will not be considered.