Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY
Jacob Eisinger

Jacob Eisinger
Director, Data, Talroo


Jacob Eisinger is the director of data at Talroo, where he is responsible for the Special Projects initiative to pilot and validate high-impact business models and technologies. Previously, Jacob led search, personalization, data warehouse, bot detection, and machine learning at Talroo and worked in the Emerging Technologies Group at IBM, where he worked with technologies like BlueMix, Apache Spark, Apache Kafka, OAuth, and web service standards. Jacob is an accomplished inventor with over 20 patent applications. He holds a bachelor’s degree in computer science from Virginia Tech.


2:00pm–2:40pm Thursday, 09/13/2018
Location: 1A 15/16 Level: Intermediate
Secondary topics:  Deep Learning, Media, Marketing, Advertising
Guoqiong Song (Intel), Wenjing Zhan (Talroo), Jacob Eisinger (Talroo )
Can the talent industry make the job search/match more relevant and personalized for a candidate by leveraging deep learning techniques? Guoqiong Song, Wenjing Zhan, and Jacob Eisinger demonstrate how to leverage distributed deep learning framework BigDL on Apache Spark to predict a candidate’s probability of applying to specific jobs based on their résumé. Read more.