Tennis Data Scientist

🕒 March 20

🏄 California – Remote

🏄 California – Remote

💵 $135k - $190k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📊 Data Scientist

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Swish Analytics

WebsiteLinkedInAll Job Openings

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.

📋 Description

• 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 • Demonstrated experience developing models at production scale for Tennis or sports betting for 2+ years • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods • 5+ 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.