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Data Scientist Assistant - NHL

$15 per hour

Tampa Bay Lighting

In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen. 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. #J-18808-Ljbffr

Vacancy posted 3 days ago
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