Many companies struggle with data science project development and deployment. In these cases, the majority of data scientists’ time is often spent on data exploration and data preparation. Data processing is time consuming and may even require months to re-code the model in the production system for deployment. In this talk, you will learn how Alliance Data has accelerated data science. By leveraging big data engineering, Alliance Data is able to streamline data acquisition, build out repeatable and scalable data ingestion and curation pipeline, automate feature engineering and use a variety of tools to speed up model development and deployment.
About the Speaker
Nan Li has more than 17 years of experience in data management, analytics and data science. As the Sr. Manager, Data Strategy and Management in the Enterprise Data Science and Analytics department at Alliance Data, Nan is responsible for leading data analytics strategy, rolling out self-service analytics, and building and expanding big data lab. Additional responsibilities include establishing a new data engineering team, consolidating data supply chain management, and implementing best practices in data stewardship. Prior to joining Alliance Data, she held positions as Director of Data Science at Nationwide and Director of Solutions and Analytics at Cardinal Health.