Data Scientist with Colorado Avalanche- Contract
Kroenke Sports & Entertainment
Denver, CO, US
Remote
2026-07-03
Announced salary
$70,000 - $85,000
Low
$87K
Median
$114K
High
$151K
Market in Denver · BLS OEWS 2025
Estimated net pay
$4,644 - $5,468
/month · 20% withheld
after tax & contributions · Single, no dependents
Job description
**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
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**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
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