
11 - 50 employees
Founded 2014
💼 Consulting
📣 Marketing
🎲 Gambling
💰 $6.9M Series B - Swish Analytics on 2019-05
Consulting • Marketing • Gambling
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.
🕒 July 22
🌐 United States, Canada – Remote
🏄 California – Remote
💵 $150k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
📊 Data Scientist
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11 - 50 employees
Founded 2014
💼 Consulting
📣 Marketing
🎲 Gambling
💰 $6.9M Series B - Swish Analytics on 2019-05
Consulting • Marketing • Gambling
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.
• Develop infrastructure for trader automation and system performance tracking • Develop high-performance and low-latency products that react to external and internal signals • Analyze live-streaming data and turn it into actionable decisions • Design and set up tests to detect unexpected model changes resulting from manual interactions • Build, test, debug, and deploy production-grade components • Develop and improve machine learning and statistical models driving core algorithms and simulation outputs • Develop contextualized feature sets using sports-specific domain knowledge • Contribute across model development stages, from proof-of-concept and beta testing through deployment with data engineering and product teams • Improve model performance through rigorous experimentation • Assess model performance, identify weaknesses, and direct development efforts • Document work and present it clearly to technical and non-technical partners
• Bachelor's degree in Data Science, Statistics, Computer Science, Applied Math, or a related technical field • Master's degree strongly preferred • 4+ years developing and delivering effective machine learning and/or statistical models for real business needs in sports analytics or sports betting • Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods • Excellent analytical and problem-solving ability • Demonstrated drive to learn quickly in unfamiliar territory • Experience with Python and relational SQL • Strong foundation with source control, including GitHub, and related CI/CD processes • Strong foundation working in AWS environments • Ideal candidates will have experience with Kafka, Docker, and Kubernetes • Ability to partner across teams on complex, ambiguous problems and communicate clearly with technical and non-technical audiences • Remote from the USA or Canada • Successful completion of background and reference checks may be required
Apply Now🕒 July 22
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