Senior Data Scientist

Edmonton Oilers; Alberta; On-site; CAD 90,000 - 120,000; Full time

Job summary

A leading NHL organization in Canada is seeking a Senior Data Scientist for their Hockey Analytics & Technology group. The role involves developing advanced machine learning models to enhance player evaluation and team strategy. Candidates should have a Bachelor's degree in Data Science or related fields and over 5 years of experience in data science, preferably in sports. Strong skills in Python, MLOps, and experience with Azure and Databricks are essential. Join a fast-paced environment that values innovation and collaboration.

Benefits

Competitive salary and benefits package

Qualifications

• 5+ years in data science or analytics, ideally within sports.
• Deep familiarity with hockey metrics and analytics.
• Experience with machine learning algorithms and ETL pipelines.

Responsibilities

• Develop ML models for player evaluation and game strategy.
• Lead R&D for new analytics models.
• Collaborate with developers and domain experts.

Skills

Python (pandas, scikit‑learn, numpy)

MLOps/ModelOps

Data Science

Statistical modeling

Communication skills

Education

Bachelor’s degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics

Tools

Azure

Databricks

PowerBI

Streamlit

Job description

In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow‑up screen.

OEG Sports & Entertainment delivers North America’s leading sports and entertainment experiences to connect our fans to their passions. Located in the heart of the ICE District, OEG owns the 5‑time Stanley Cup Champion Edmonton Oilers, the WHL’s three‑time Memorial Cup Champion Edmonton Oil Kings, and the AHL’s Bakersfield Condors. OEG operates Rogers Place, North America’s premier and most technologically advanced sports and entertainment venue. The 18,647 seat, $480 million arena is among the most technologically enabled sports facilities in North America as well as the first LEED Silver‑certified NHL Facility in Canada.

Our vision is to be a Global Leader in Sports & Entertainment. Together, we inspire our fans by connecting them to their passions, which is ours as well! We play hard as a team, and with devoted integrity towards our common purpose. We have commitments to innovation and growth, combined with performance excellence that ensures a fair return on investment. We develop our people to be leaders in our industry, and we invest in our communities. Through our world class talent, we strive toWIN. ON and OFF the ICE.

About the Role

The Edmonton Oilers Hockey Club, a premier NHL organization, is building a new Hockey Analytics & Technology group to push the boundaries of data‑driven decision‑making in hockey. The group will leverage all aspects of technology (including data, analytics, and software development) to enhance player evaluation, team strategy, and overall performance. This work will directly impact organizational decision‑making and the long‑term competitiveness of the team.

As a Senior Data Scientist in the Hockey Analytics & Technology group, you will play a pivotal role in developing advanced machine‑learning (ML) models that provide actionable insights for executives, scouts, and coaches. This role will leverage large‑scale historical datasets in player tracking, game events, and scouting reports to create these models, where the only constraint is your creativity. You will work on cloud platforms and Databricks to perform R&D, build scalable data science pipelines, and deploy your machine‑learning models. You'll also collaborate with the larger team to create compelling end products for our internal web application using the outputs you’ve created.

The successful candidate will be a knowledgeable practitioner in MLOps via MLFlow for managing machine‑learning workflows. A deep understanding of ML algorithms, high‑dimensional data, and experience in rapid development of prototypes will be critical.

Your Focus in this Role

• Lead development and deployment of machine‑learning models for player evaluation, game strategy, and operational decisions.
• Drive R&D efforts to develop next‑generation models using large‑scale experimental datasets, exploring novel approaches that push the boundaries of what’s possible in hockey analytics.
• Implement scalable workflows using Azure and Databricks, with a focus on model deployment.
• Oversee MLOps/ModelOps processes, including MLFlow for tracking experiments, model versioning, and deployment.
• Collaborate with Developers and domain experts to design data‑driven products and ensure insights are delivered visually in engaging formats via our internal web application.
• Use appropriate toolsets (such as PowerBI, Notebooks, or Streamlit) to communicate ad‑hoc prototypes and Proof of Concepts before moving things towards production.
• Optimize, enhance, and scale existing predictive models and deploy them for real‑time usage.
• Stay current with machine‑learning advancements to continually push the team’s capabilities.

Qualifications

• Education: Bachelor’s degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics, or related field (Master’s or PhD considered assets).
• Experience: 5+ years in data science or analytics, ideally with a focus on sports or performance data.
• Technical Skills:
• Proficiency in Python (pandas, scikit‑learn, numpy) and/or R for statistical modeling and analysis.
• Experience with Azure cloud services and Databricks for big data management and model deployment.
• Expertise in MLOps/ModelOps, with experience using MLFlow for model management.
• Knowledge of basic statistics, simulation, optimization algorithms, and an overall analytics tool‑belt is considered a major asset.
• Experience with high‑dimensional data modeling.
• Comfortable using tools such as PowerBI, Jupyter notebooks, Streamlit, or Plotly to communicate model outputs, visualize insights, and build rapid prototypes.
• Experience with light data engineering tasks such as building ETL pipelines and transforming data as required for modeling input.
• Deep experience with machine‑learning algorithms (e.g., random forests, neural networks, gradient boosting) is a requirement. Knowledge of deep learning frameworks (TensorFlow, PyTorch, Keras, etc.) considered an asset.
• Hockey Knowledge: This is a dream role for hockey modeling obsessives. We want someone who lives and breathes hockey analytics—whether that means you’ve built your own expected‑goals models, scraped data to answer questions no one else is asking, or debated methodology on Twitter/X. Deep familiarity with advanced metrics (e.g., Expected Goals, WAR, Corsi, Fenwick) and the evolution of public hockey analytics is strongly preferred. Candidates who have pursued their own high‑quality hockey analytics or modeling projects are of particular interest. Experience with an existing NHL hockey analytics department is considered a major asset.
• Strong communication skills to present complex analyses to non‑technical audiences.
• Work Style: You’re a self‑starter who moves fast and iterates faster. You bring optimistic energy to the team and aren’t afraid to take bold swings on new modeling approaches. You thrive in an environment where risk‑taking is encouraged, collaboration is the default, and you’re given the time and support to iterate and successfully create the models that matter most.

Why Join Us?

• Be part of the innovative team at the forefront of hockey analytics in the NHL, where the pace of work is intense but the impact you can have is real & tangible.
• Competitive salary and benefits package.

Next Steps

Thank you for your interest in joining our team! Those moving forward in the process will be contacted by a member of our team.

Stay in Touch!

Official Edmonton Oilers Website | NHL.com