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Swish Analytics Inc. Logo

Machine Learning Engineer

Swish Analytics Inc.

$165,000 - $195,000
Nov 19, 2025
Remote, US
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Swish Analytics is looking to solve the challenge of oddsmaking, which they believe is rooted in engineering, mathematics, and sports betting expertise, not intuition. They aim to build the next generation of predictive sports analytics data products.

Requirements

  • Demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred

Responsibilities

  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

Other

  • This position is 100% remote
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues
  • All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.