Sports Data Scientist
Posted on 9/7/2023
Swish Analytics

11-50 employees

Predictive sports analytics data company
Remote in USA
Experience Level
Desired Skills
Data Analysis
Data Science
Data Structures & Algorithms
AI & Machine Learning
Data & Analytics
  • Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area; Master degree highly preferred
  • Demonstrated experience developing models at production scale for NBA, NHL, MLB, Tennis, college basketball, or college football
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • 4+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs
  • Experience with relational SQL & Python
  • Experience with source control tools such as GitHub and related CI/CD processes
  • Experience working in AWS environments etc
  • Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
  • Excellent communication skills to both technical and non-technical audiences
  • Ideate, develop and improve machine learning and statistical models that drive Swish's core algorithms for producing state-of-the-art sports betting products
  • Develop contextualized feature sets using sports specific domain knowledge
  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models
  • Strive to constantly improve model performance using insights from rigorous offline and online experimentation
  • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts
  • Adhere to software engineering best practices and contribute to shared code repositories
  • Document modeling work and present to stakeholders and other technical and non-technical partners