Tennis Data Scientist

Duties

• 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.
• Demonstrated experience developing models at production scale for Tennis or sports betting for 2+ years.
• Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods.
• 5+ 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 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.

Pay

Base salary: $135,000 - $190,000

Schedule

Remote from the USA