WorldQuant Predictive’s customers rely on our predictions to understand how changing world and market conditions will impact decisions to be made. Speed is critical, and so are accuracy and resilience. To that end, our data team built a modern, automated MLOps data flow using Databricks as a key part of our data science tooling, and integrated with Immuta to provide automated data security and access control.
In this session, we will share details of how we used policy-as-code to support our globally distributed data science team with secure data sharing, testing, validation and other model quality requirements. We will also discuss our data science workflow that uses Databricks-hosted MLflow together with an Immuta-backed custom feature store to maximize speed and quality of model development through automation. Finally, we will discuss how we deploy the models into our customized serverless inference environment, and how that powers our industry solutions.
Talk by: Tyler Ditto
Connect with us: Website: https://databricks.com
Twitter: https://twitter.com/databricks
LinkedIn: https://www.linkedin.com/company/databricks
Instagram: https://www.instagram.com/databricksinc
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