Data Scientist

🕒 July 22

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🏄 California – Remote

🏄 California – Remote

💵 $150k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• 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

🎯 Requirements

• 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