Data Scientist Assistant

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.

• 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

• 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

• Ability to work extended hours including late nights, holidays, and weekends as needed 
• This role is eligible for remote work

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.