PrizePicks is looking to develop and maintain analytics tools and workflows to support the business across all departments, with a focus on real-time simulation-based market pricing within the product.
Cloud platform services in GCP and analogous systems: Cloud Storage, Cloud Compute Engine, Cloud Functions, Kubernetes Engine
Code version control: Git
Code testing libraries: PyTest, PyUnit, etc
Common ML and DL frameworks: scikit-learn, PyTorch, Tensorflow
MLOps tools: DataBricks, MLFlow, Kubeflow, DVC
Responsibilities
Create and maintain optimal sport data stream architecture
Partner with Data Science to determine best paths for operationalization of DS/ML assets
Steer the design, implementation, and deployment of the data, MLOps, and API stack
Partner cross-functionally with Engineering, QA, and Product teams to enable the creation and distribution of highly visible and real-time data products
Empower teams to build and own rigorous monitoring, alerting, and documentation processes
Act as a thought leader in the broader PrizePicks technology org
Other
7+ years of experience in Backend Engineering/Machine Learning Engineering
3+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers and scientists
Excellent organizational, communication, presentation, and collaboration experience with organizational technical and non-technical teams
Graduate degree in Computer Science, Statistics, Mathematics, Informatics, Information Systems or other quantitative field
