Underdog is looking to build out its foundational Machine Learning platform to accelerate model building and deployment processes.
Requirements
- At least 5 years of experience with model lifecycle (optimization, training and serving) in a cloud environment
- Advanced proficiency with Python and SQL
- Strong proficiency with SageMaker, Vertex AI, Databricks, Kubeflow and/or comparable ML platforms or technologies
- Knowledge of statistical concepts such as univariate and bivariate distributions, regression models, and binomial models
- Experience with data technologies like Airflow, Dagster, Spark, and/or dbt
Responsibilities
- Build out our foundational Machine Learning platform
- Build internal tools and services to accelerate UD’s model building and deployment process
- Build frameworks to measure and analyze model performance and accuracy in production environments
- Lead technical initiatives, and drive results in a fast-paced, dynamic environment
- Lead code reviews, provide constructive feedback, and evangelize best practices to maintain code and data quality
- Keep up to date on emerging ML technologies and trends and focus on iteratively implementing them into Underdog’s engineering systems
Other
- Highly focused on delivering results for the Data Science team in a fast-paced, entrepreneurial environment
- Strong interest in sports
- Prior experience in the sports betting industry
- This position may require sports betting licensure based on certain state regulations.
