Keria is a data scientist in the Data Strategy team of Showtime Networks Inc, where she works building data pipelines in Spark, analytical tools, and machine learning models with the goal of assisting teams across the company. The data and consumer insights generated by her and the Data Strategy team sustain data-driven decisions in the SHOWTIME over-the-top subscription service.
Before joining SHOWTIME, Keria was an Insight Data Science postdoctoral fellow. Prior to becoming a data scientist Keria was a postdoctoral fellow at NYU School of Medicine where she worked as a researcher and built computational tools and published several papers in bioimage informatics and Neuroscience. Keria completed a Ph.D. in Physiology and Neuroscience from New York University on 2015. Keria is based in the SHOWTIME offices in New York.
Interested in learning how Showtime is leveraging the power of Spark to transform a traditional premium cable network into a data-savvy analytical competitor? The growth in our over-the-top (OTT) streaming subscription business has led to an abundance of user-level data not previously available. To capitalize on this opportunity, we have been building and evolving our unified platform which allows data scientists and business analysts to tap into this rich behavioral data to support our business goals. We will share how our small team of data scientists is creating meaningful features which capture the nuanced relationships between users and content; productionizing machine learning models; and leveraging MLflow to optimize the runtime of our pipelines, track the accuracy of our models, and log the quality of our data over time. From data wrangling and exploration to machine learning and automation, we are augmenting our data supply chain by constantly rolling out new capabilities and analytical products to help the organization better understand our subscribers, our content, and our path forward to a data-driven future.