Data Scientist

Summary

Join Swish Analytics, a sports analytics startup, as a Data Scientist and contribute to the development of cutting-edge sports betting products. This remote position, based in the USA, involves creating and improving machine learning models, developing feature sets using sports domain knowledge, and collaborating with engineering and product teams. You will be responsible for all stages of model development, from proof-of-concept to deployment, and will analyze results to enhance model performance. The ideal candidate possesses a Master's degree in a relevant field, extensive experience in model development for sports or sports betting, and strong communication skills. A competitive base salary is offered.

Requirements

• Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
• Demonstrated experience developing models at production scale for football, basketball, baseball, hockey, soccer, tennis, or sports betting
• 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 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. 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

Benefits

Base salary: $107,000-175,000