Data Science Careers in Machine Learning & Artificial Intelligence
Monday, November 15, 2021, 5:30 – 6:30 PM CST
Back in 2012, the Harvard Business Review called data science “the sexiest job of the 21st century.” Even today, data science continues to be a rapidly growing & evolving field. Join our special seminar to learn more about data science careers (specifically, machine learning & AI), the difference between data scientist & data engineer, the types of roles/positions that exist within this field, and so much more!
Our panelists will discuss what drew them to the field, types of projects that populate their days, the competencies that are required to be successful in these types of careers, and their advice for how to use your scientific training to support your entry into this career path.
Alexandra Cunliffe, PhD
Machine Learning Engineer, Prolego
Alex Cunliffe is an AI developer with an interest in applying deep learning to diverse industry settings. She received a PhD in Medical Physics at the University of Chicago in 2014. Following graduation, Alex spent 6 years working as a Data Scientist at 3M, where she deployed multiple 3D computer vision models and robotic path planning algorithms for orthodontic treatment planning and filed 17 patents. She currently works as a Machine Learning Engineer at Prolego, a small AI consulting start-up that specializes in helping Fortune 500 companies solve problems with machine learning.
Matthew Green, PhD
Machine Learning Engineer, co-op commerce
I got my PhD at University of Chicago in 2012 in the Computational Neuroscience program. I worked as a postdoc at Northwestern for about 3 years, before quitting to find opportunities in software engineering. I spent about 6 months working on a new startup with two other people I met via a friend. At that time, I was not taking in a salary so I switched to working at a later stage startup as a fulltime backend/data engineer. Later I worked for about 2 years as a data engineer at Trunk Club and then moved into a data science role. Because of covid, Trunk Club was absorbed into Nordstrom and I worked for about a year as a data scientist at Nordstrom where I applied deep learning to automating outfit building. I now work for an early stage startup called co-op commerce as a machine learning engineer. Co-op is based in San Francisco but my role is completely remote. Currently I build and maintain recommender systems and other models that identify the best new customers for brands. I live in Chicago and have two kids and a cat.
Ali Vanderveld, PhD
Senior Staff Data Scientist, Wayfair
Ali Vanderveld received her PhD in Physics from Cornell University in 2007, and went on to work as a Postdoctoral Scholar at Caltech and then as a KICP Fellow at the University of Chicago. During this time she studied the large scale Universe and worked on the development teams for several space telescope missions, including ESA’s Euclid. Ali switched from Physics to Data Science in 2013, subsequently working for Groupon, Civis Analytics, ShopRunner, Amazon, and now Wayfair. She also spent a summer as a technical mentor for the Data Science for Social Good Fellowship at the University of Chicago. In her current role as Senior Staff Data Scientist, Ali is a technical leader for Machine Learning at Wayfair, currently leading the development of novel search and recommendation technologies.
