Key skills
Machine LearningStatistical ModelingData ValidationData VisualizationFeature EngineeringModel TrainingModel EvaluationModel DeploymentPythonSQLMySQLKubernetesCI/CDCloud-native EDWETLLarge Scale Data ProcessingQuantitative AnalyticsTradingRustData EngineeringAnalyticsCommunicationCollaboration
About this role
Swish Analytics is a sports analytics startup focused on predictive sports analytics data products. They are seeking an experienced Machine Learning Engineer to build and optimize machine learning frameworks and support various sports-related data challenges.
Responsibilities:
- 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
- Experience applying large scale data processing techniques to develop scalable and innovative sports betting products
- 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
- A proven background in quantitative analytics, trading, or engineering is required for this position
- 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
- 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
- Background and/or interest in Rust