About the position
Swish Analytics is hiring Basketball Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. We're hiring a Data Scientist to support our Sports Data Models.
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.
Requirements
- Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area; PhD highly preferred.
- Demonstrated experience developing models at production scale for baseball or sports betting.
- Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods.
- Minimum of 4+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs 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.
- Proven track record of strong leadership skills.
- Excellent communication skills to both technical and non-technical audiences.
Benefits
- Base salary: $120,000-175,000 (encompasses multiple levels and depends on experience)
