{SPORT} Data Scientist

Swish Analytics

$100K — $140K *
Media
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS/BA in Mathematics, Computer Science, or related STEM field
  • 2+ years of experience writing production-level code in Python
  • Proficient in Python and SQL, preferably MySQL
  • Experience with Airflow and Kubernetes
  • Skilled in building end-to-end ETL pipelines
  • Familiar with REST APIs and version control (git)
  • Knowledgeable in cloud computing infrastructures like AWS
  • Understand web scraping and cleaning unstructured data
  • Familiar with data science and machine learning
  • Strong interest in sports, particularly Tennis, and knowledge of US sports leagues.

Responsibilities

  • Support production systems during live sporting events
  • Architect real-time analytics systems for data collection and feature development
  • Create new sports betting data products and prediction offerings
  • Integrate complex real-time datasets into products
  • Develop enterprise-grade APIs for predictive analytics
  • Design and implement automated sports data delivery frameworks

Benefits

  • Fully remote position
  • Opportunity to work on cutting-edge technology
  • Direct impact on core data offerings
  • Chance to contribute to the sports data industry
  • Work within a passionate and dedicated team
Full Job Description
Job Description

The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.

Duties
  • Support production systems and help triage issues during live sporting events
  • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
  • Build new sports betting data products and predictions offerings
  • Integrate large and complex real-time datasets into new consumer and enterprise products
  • Develop production-level predictive analytics into enterprise-grade APIs
  • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Requirements
  • BS/BA degree in Mathematics, Computer Science, or related STEM field
  • Minimum of 2+ years of demonstrated experience writing production level code (Python)
  • Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow
  • Demonstrated experience with Kubernetes
  • Experience building end-to-end ETL pipelines
  • Experience utilizing REST APIs
  • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
  • Experience with web scraping and cleaning unstructured data
  • Knowledge of data science and machine learning concepts
  • A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets

Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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