Swish Analytics
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.
Sports Data Analyst
🕒 April 28
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Swish Analytics
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.
📋 Description
• Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data • Source origins of data inaccuracies through data pipeline dependencies and python code base • Define data validation tests to flag future game errors • Research accurate roster active statuses, primary positions and game participation • Validate data changes after logic updates • Production model feature deep dives to explain project market lines • Clearly document findings • Develop intimate familiarity with existing databases and construct metadata references • With guidance, support lead Data Scientists in feature development and model analysis
🎯 Requirements
• Bachelor's Degree in Computer Science, Data Science or similar major • Minimum of 1 year of experience in football data analysis • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios • Data Extraction, Wrangling and Analysis in Python • Strong SQL querying skills • Attention to detail
🏖️ Benefits
• Health insurance • Remote work options
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