{SPORT} Data Scientist

Swish Analytics

$90K — $130K *
US-AnywhereRemote in San Francisco, CA
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 in writing production-level code, specifically in Python.
  • Proficient in SQL, preferably MySQL, and experienced with Apache Airflow.
  • Hands-on experience with Kubernetes for container orchestration.
  • Skilled in building end-to-end ETL pipelines and utilizing REST APIs.
  • Familiar with version control (git), CI/CD processes, and cloud infrastructures like AWS.
  • Knowledgeable about web scraping and handling unstructured data.

Responsibilities

  • Support production systems and address issues during live sports events.
  • Architect real-time analytics systems for data collection and feature production.
  • Build and enhance sports betting data products and prediction offerings.
  • Integrate complex real-time datasets into consumer and enterprise tools.
  • Develop predictive analytics into enterprise-grade APIs.
  • Contribute to automated frameworks for sports data delivery.

Benefits

  • Fully remote position, offering flexibility.
  • Opportunity to work with cutting-edge technologies and sports data products.
  • Engaging and passionate team focused on accurate predictions and real-time data.
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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