You are viewing a preview of this job. Log in or register to view more details about this job.

Part-Time Data Scientist Assistant

Compensation: $15 per hour

Tentative Start Date: September 1, 2026

Time Commitment: 2026-2027 NHL Season - Approximately 20/25 hours per week

 

Job Summary       

The Part-Time Data Scientist Assistant supports the hockey analytics department by applying advanced data analysis to drive insights and inform decision‑making. The position works closely with hockey data to execute assigned analytical initiatives, develop new projects, and translate complex findings into clear, actionable insights for both technical and non‑technical audiences. As part of a collaborative, team‑based environment, this role contributes to scalable, impactful solutions while supporting an innovative, growth‑minded culture within the organization.

Essential Duties & Responsibilities

Work with hockey data to fulfill assigned analytical directives and contribute to ongoing projects

Design, develop, and execute new analytics projects that generate actionable insights

Analyze data using geometric, physical, and statistical concepts relevant to hockey performance

Interpret analytical results and clearly communicate findings to technical and non‑technical stakeholders

Collaborate effectively within a team‑based hockey analytics environment

Contribute to impactful, scalable solutions in a growth‑minded and innovative culture

Other duties as assigned

 

Qualifications

Degree or academic background in Computer Science, Mathematics, Engineering, Physics, or a related field

2–3 years of experience writing modern Python code

Experience working with SQL databases

Familiarity with Git or other version control systems

Ability to perform geometric and physics‑based analyses

Strong problem‑solving skills with a demonstrated desire for continuous learning and professional development

Experience working in a collaborative, team‑based environment

Strong ability to interpret data and communicate results effectively

Knowledge of statistics and probability theory preferred

Experience working with time‑series data and/or skeletal or player‑tracking data preferred

Familiarity with machine learning concepts and practical applications preferred

Experience with advanced statistical modeling techniques preferred

Prior experience working with sports or hockey‑related data preferred

 

Working Conditions

Ability to work extended hours including late nights, holidays, and weekends as needed 

This role is eligible for remote work