Senior Data Scientist - NHL

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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 to
WIN. ON and OFF the ICE.

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.

• 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/Model Ops 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 Power
  
  BI, 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.

• 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…