
11 - 50 employees
Founded 2014
🎲 Gambling
🤖 Artificial Intelligence
🤝 B2B
💰 $6.9M Series B - Swish Analytics on 2019-05
Gambling • Artificial Intelligence • B2B
Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.
🔥 0 minutes ago
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11 - 50 employees
Founded 2014
🎲 Gambling
🤖 Artificial Intelligence
🤝 B2B
💰 $6.9M Series B - Swish Analytics on 2019-05
Gambling • Artificial Intelligence • B2B
Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.
• Support production systems and help triage issues during live sporting events • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production • Build new sports betting data products and predictions offerings • Integrate large and complex real-time datasets into new consumer and enterprise products • Develop production-level predictive analytics into enterprise-grade APIs • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks
• BS/BA degree in Mathematics, Computer Science, or related STEM field • Minimum of 2+ years of demonstrated experience writing production level code (Python) • Proficiency in Python and SQL (preferably MySQL) • Demonstrated experience with Airflow • Demonstrated experience with Kubernetes • Experience building end-to-end ETL pipelines • Experience utilizing REST APIs • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS) • Experience with web scraping and cleaning unstructured data • Knowledge of data science and machine learning concepts • A strong interest in sports and sports betting, with an emphasis on Tennis. • An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets.
• Equal Opportunity Employer
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