Job description

Company Overview Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients. 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 Base Salary: Starting at $160,000 - DOE Swish Analytics is an Equal Opportunity Employer. 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. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.

Requirements

Must-haves

Company Overview
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
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
Base Salary: Starting at $160,000 - DOE

Nice-to-haves

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Keywords to mirror

pythonsqlkubernetesrestawsmachine learning

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