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Sport Data Scientist
Swish AnalyticsData Engineer at Swish Analytics building predictive analytics systems for sports betting. Supporting infrastructure and delivering data offerings for various clients in a remote role.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing low-latency, real-time analytics systems and production-level predictive analytics, with a strong foundation in Python, SQL, and cloud-computing infrastructures. Possesses a deep understanding of sports data and the ability to integrate complex datasets into consumer and enterprise products.
Highest-signal resume keywords
Python ProgrammingSQL ProficiencyKubernetes ExperienceAirflow KnowledgeETL Pipeline Development
ATS Keywords
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Hard Skills
Production Level Code WritingData Science ConceptsMachine Learning ConceptsWeb ScrapingData CleaningREST API UtilizationShell ScriptingVersion Control (Git)Continuous IntegrationCloud Computing (AWS)
Industry Keywords
Sports BettingReal-Time AnalyticsSports Data Delivery FrameworksComplex DatasetsTennis KnowledgeUS-Based Sports Knowledge
Tech Stack
Tools & technologiesAirflowAWSCloudETLKubernetesMySQLPythonShell ScriptingSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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 to use your knowledge of the sport to inform your work with complex datasets
Benefits
Comp & perks- Health insurance
- Professional development opportunities