FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Build and transform new data sources into tables, features, and structures that are easy for the team and our clients to build on
- Develop, extend, and validate models — including event-probability models and athleticism models — ensuring data representation supports both current and future use cases
- Build metrics and analyses that NHL and NBA clients rely on to make decisions, and support client-facing work by digging into the data to answer their questions directly
- Extract meaningful features from high-dimensional tracking and pose data, and update existing models to incorporate new signals as they become available
- Validate models and outputs — your own and others' — with enough rigor that the team can trust what ships
- Write clear reports that communicate technical work to the product team and broader organization
Requirements
What you’ll need- 3+ years of experience working with sports tracking data including the kinds of models typically built and the data challenges that come with them
- Strong data science fundamentals: you understand how models work, what they need from the data, and how to set data up to support them
- Proficiency in Python or R, with solid statistical foundations and comfort with SQL for building and querying structured data
- Attention to detail in how data is structured and represented, with an eye for edge cases, consistency, and how downstream users will interact with what you build
- A team-first mentality — both teams are small, and being someone others can rely on matters as much as technical skill
- For Hockey: direct experience with hockey data or hockey analytics (inside a team, public work, or academically), and familiarity with pose or skeleton data or other high-dimensional spatiotemporal data sources
- For Basketball: experience working inside an NBA front office or comparable environment, familiarity with deep learning methods, and public-facing basketball analytics work that demonstrates how you think about the game.
Benefits
Comp & perks- Offers Equity
- Offers Bonus
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data modelingevent-probability modelsathleticism modelsfeature extractiondata validationPythonRSQLstatistical analysisdeep learning
Soft Skills
attention to detailteamworkcommunicationproblem-solvingreliability