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 enterprise clients.

In Short

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.

Requirements

Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area.
5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs.
Demonstrated experience developing data science modeling systems and infrastructure at scale.
Experience with Python and exposure to modern machine learning frameworks.
Proficient in SQL; experience with MySQL.
Background and interest in Rust preferred.
Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback.
Strong communication skills when discussing technical concepts with technical and non-technical colleagues.