Sports Data Scientist
Posted on 9/7/2023
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
AWS
Data Analysis
Data Science
Data Structures & Algorithms
Git
SQL
Python
CategoriesNew
AI & Machine Learning
Data & Analytics
Requirements
- 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
Responsibilities
- 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