United States onlyCompany Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
Swish Analytics is looking for an NHL Data Scientist 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.
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
- Minimum of 1+ years of experience developing hockey or sports betting models at production scale
- Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
- Minimum of 1+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs
- Expertise with NHL rules and game flow
- 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
