The job of a data scientist has been declared as one of the most lucrative jobs of the 21st century by our very own alumnus and CDS of the US, DJ Patil*, and many others. Today, almost every company is trying to make sense out of it’s data and hire data scientists. But, industry and academia do not yet agree on what data scientists are. Do they do math or statistics or computer science theory or optimization? Is data science about optimization or algorithms or statistical models or engineering? Is it systems engineering and data pipelining and feature engineering? In this talk, I will discuss how computer scientists can become data scientists and what being a data scientist means from my own and my team’s experience working in the field. I will talk about how graduate students in Computer Science are uniquely positioned to do this job well, and what we can learn from school and what can be learnt from being in the trenches. To end the talk, I will go over my team’s work in Real Time Bidding for Display Ads, and discuss what it is like to work for Adobe.
*(https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century/)
Neha Gupta works as a Data Scientist in the Algorithms team at Adobe Media Optimizer which is a part of Adobe Digital Marketing. She graduated with her Ph.D in Computer Science from University of Maryland, College Park in 2012. She has published several papers in the area of large scale machine learning, online learning and location determination technologies. In general, her interests lie in applying machine learning and data mining to build smarter products. Before joining graduate school, she worked for Samsung as a Software Engineer for two years in their Telecom and Networks division. She finished her undergraduate studies in Electronics Engineering from Indian Institute of Technology, Banaras Hindu University, India. Neha is a TED fellow, and believes in the power of ideas.