• 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. • Use extensive experience to build, test, debug, and deploy production-grade components. • Participate in development of database structures that fit into the overall architecture of Swish systems