Clash
of Jobs
Browse All Jobs
Job Description
Swish Analytics is seeking a Soccer Data Scientist to join their expanding team. This role is central to the company's operations, focusing on the development of core data products. The Data Scientist will support sports data models, contributing to the creation of state-of-the-art sports betting products.
Role involves:
- Ideating, developing, and improving machine learning and statistical models.
- Developing contextualized feature sets using domain knowledge in soccer.
- Contributing to all stages of model development, from proof-of-concept to deployment.
- Improving model performance through experimentation.
- Analyzing results to identify model weaknesses.
- Adhering to software engineering best practices and contributing to shared code repositories.
- Documenting modeling work and presenting to stakeholders.
Requirements:
- Masters degree in Data Analytics, Data Science, Computer Science, or related field.
- Experience developing models at production scale for soccer or sports betting.
- Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods.
- Minimum of 3+ years of experience developing and delivering effective machine learning and/or statistical models in sports or sports betting.
- Experience with relational SQL & Python.
- Experience with source control tools such as GitHub and related CI/CD processes.
- Experience working in AWS environments.
- Strong leadership and communication skills.
Role offers:
- Opportunity to work on core components of Swish's data products.
- Impact on developing state-of-the-art sports betting products.
- Collaboration with data engineering and product teams.
