Data Scientist with Colorado Avalanche- Contract at Legends at Ball Arena

Quinte West, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

01 Oct, 26

Salary

85000.0

Posted On

03 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

R, Python, Predictive Modeling, Data Visualization, SQL, Relational Databases, Azure, AWS, Shiny, Power BI, Machine Learning, Spatio-temporal Data Analysis, Statistical Modeling, Communication Skills, Probabilistic Thinking

Industry

Spectator Sports

Description

Job Title: Data Scientist with Colorado Avalanche Department: Colorado Avalanche, Hockey Ops Location: Denver, Colorado is preferred, but could be remote (with Occasional Travel) Reports to: Data Scientist Employment Type: Full Time- Employment Contract- Salary Supervisor Position: No Posting End Date: 7/20/2026 ________________________________________________________________________ Position Overview: The Colorado Avalanche are looking to hire a full-time data scientist to work within the team’s Hockey Operations Department. This person will use their knowledge of statistical best practices and modeling techniques to analyze large datasets and present takeaways in fields such as: player and team evaluation, in-game tactics, and roster building. They will have the opportunity to work with advanced event, tracking level, and biometric datasets and will work closely with various members of the hockey operations department. Location: Denver, Colorado is preferred, but could be remote (with occasional travel) Responsibilities: * Research, develop, and test predictive models for player evaluation and projection at all levels * Work with large datasets to answer questions for decision-makers including coaches and management * Create data visualizations, reports, profiles, and presentations that communicate methodology and key findings to audiences with a range of technical competencies * Collaborate with our team of analytics and hockey operations personnel to best complete projects and support our management group * Respond to analytics or hockey operations personnel questions and project requests in a timely fashion including at times on evenings and weekends Required Qualifications: * Ability to think probabilistically and comfort dealing with uncertainty * Expertise in one or multiple coding language, preferably R and Python * Experience building predictive models of various types from large, complex datasets * Strong verbal and written communication skills Preferred Qualifications: * 1-3 years of work experience in a data analysis and/or modeling-related position * An advanced degree in computer science, applied mathematics, predictive analytics, statistics, or a related field * Expertise in AI, machine learning, and building models with spatio-temporal data * A comfort level working with SQL and relational databases in a cloud computing environment, preferably Azure or AWS * Experience building dashboards, web applications, and interactive data visualizations, which can include working in Shiny or Power BI * Knowledge of NHL players and teams as well as a passion for hockey and hockey analytics Compensation: * Salary Range: $70k-$85k, Contract Employee Applications must be received by: 07/20/2026 Equal Employment Opportunity Kroenke Sports & Entertainment (KSE) provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Develop and test predictive models for player evaluation and roster building within the Hockey Operations Department. Create data visualizations and reports to communicate key findings to coaches and management.