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Data Scientist Assistant - NHL
Tampa Bay Lightning
- Tampa, Florida, United States
- Tampa, Florida, United States
About
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
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.
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Languages
- English
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