Wednesday night, June 24, there were 54 MCIT students registered to hear from V.P. of Data Science at Spectrum Labs, Jon Purnell, and the event did not disappoint. Jon was gracious with his time and with sharing from his experiences as a Data Scientist.
We received a definition of terms: Data Science vs. Machine Learning (ML) vs Natural Langauge Processing (NLP) and a breakdown of roles: Data Scientist vs Data Analyst vs Data Engineer. Clarity on this alone was worth the price of admission (which was free, by the way – all our events are).
Jon talked about his company, Spectrum Labs, and how they use data to help keep the web safe from in chatrooms, discussion boards and even dating sights. He provided feedback on what he looks for in hiring new Data Scientists and how the skills of a Software Engineer do and do not overlap with the Data world.
And finally, we addressed bias and fairness in analyzing data. This topic could easily be a multi-hour conversation on its own, but Jon left us with a great summary of the topic.
The conversation could have continued on for much longer, but we simply ran out of time. Jon has provided an open invitation to anyone who watches the recording (or anyone who did not get their question answered live) to send questions. He’ll do his best to address them in an article he is writing up in response to our conversation. You can send those questions to mandlerm@seas.upenn.edu
About the Speaker:
Jonathan Purnell is the VP of Data Science at Spectrum Labs. Formerly, as a Data Scientist for Krux and Salesforce DMP, Jon delivered Internet-scale distributed products using innovative machine learning techniques, including Deep Learning and NLP. Before that, he was an Applied Scientist at Bing Ads and a collaborative researcher with BBN Technologies (a division of Raytheon). He holds a Ph.D. in computer science focused on machine learning.
About Spectrum Labs:
Spectrum Labs develops AI solutions that help consumer-facing companies recognize and respond to harmful user-generated content and behaviors. The company helps social, dating, gaming, and e-commerce platforms to help moderate user interactions and provide a safer environment for their customers.