Job description
- Quantify, evaluate, and project the performance and abilities of hockey players and teams
- Build, validate, and automate models for hockey player and team performance using multiple data sources
- Collaborate with a team of data scientists, data engineers, and hockey operations personnel
- Prepare written and/or automated reports for presentation to hockey operations personnel
- Creatively use existing data to advance our understanding of the sport of hockey, the performance of players and teams, etc
- Bachelor’s degree or higher in statistics, data science, machine learning, computer science, mathematics, or a related field
- Strong knowledge of programming for data analysis, preferably using R
- Demonstrated experience working with large, complex datasets
- Experience building a variety of statistical models, and an understanding of those models
- Experience writing shared code and using version control tools in team work environments
- Enthusiasm to work for a professional sports team
- 1+ years of experience as a data scientist (preferably with prior experience in sports analytics) and/or sufficient experience working professionally in sports analytics
- Portfolio of projects available to be reviewed during the interview
- Deep understanding of (and demonstrated experience building) a variety of statistical models (e.g. generalized linear models, generalized additive models, hierarchical models, mixture models, non-parametric models, tree-based models, Bayesian models and MCMC, bagging, boosting, supervised learning, unsupervised learning, neural networks, time series models, etc)
- Experience analyzing and building models with spatio-temporal data
- Strong knowledge of hockey and/or sports analytics
- Basic proficiency with SQL or basic understanding of modern database architectures and data structures
- Experience building dashboards, web applications, and/or interactive data visualizations with any tool (e.g. HTML, CSS, JavaScript, Shiny, Tableau, etc)
- General understanding of Hockey is preferred but not required.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.