by Daniel Egger, MEMP Professor
A group of Duke MEM alumni and current students gathered at Uber world headquarters in downtown San Francisco on the evening of Monday, July 23 for the 2nd annual Silicon Valley meetup. We shared dinner, conversation, and short presentations on some of the novel data science challenges our MEM alumni are currently working on at Uber.
Attendees represented almost every graduation year from 2009 to 2019. We had a great mix of new faces, along with returnees from last summer’s gathering at Airbnb. We also had a great cross-section of the current energy in Silicon Valley, featuring people employed at venture funds, banks, consulting firms, and high-tech startups, as well as Airbnb, Facebook, Google, Salesforce, and of course Uber. It was fun to get a sense of the fascinating work our graduates are involved in, and the very rapid career progress possible today for those whose work touches on data science.
Our Uber hosts were welcoming and great speakers. Venos Sourmelis, MEMP ’13, who had organized the event, talked about the complexities of his work managing traffic flows for Uber in and out of San Francisco International Airport. Uber handles 65% of all auto transport services there.
Tucker Risman, MEMP ’14, talked about how Uber calculates estimated times of arrival (ETAs) and optimal routes thousand of times for each trip. The map data behind this service is in constant development, and requires a high degree of local knowledge for every city around the world where the company operates.
Aditya Binaykia, MEMP 14, works in product development for the “Uber eats” meal delivery service. He described the many choices involved in determining how restaurant menus are displayed, and explained the complex tradeoffs Uber faces in determining what restaurants are within a reasonable delivery radius for any given customer address.
The overall impression I took away from the Uber presentations was of a company tackling fantastically complex real-time data-analysis challenges, with obsessive dedication to mastering every possible detail of the data that drives their business.
It was great to reconnect with my former Teaching Assistants and students, and to meet new people who appreciate their connection to Duke and the MEM program. Anyone who attended this event would come away with the sense that Duke’s Master of Engineering Management Program is ideal preparation for an exciting and highly-successful data science career in Silicon Valley.
Daniel Egger has more than seventeen years experience creating new software products and services, as founder and CEO of a series of venture-backed information technology companies, and as Managing Partner in a venture capital fund. Egger is Executive in Residence in Duke University’s Master of Engineering Management Program and has taught courses in entrepreneurship and venture capital at Duke since 2003. He was formerly the Howard Johnson Foundation Entrepreneur-in-Residence in Duke’s Markets and Management Program for undergraduates.
Courses taught by Professor Egger:
EGRMGMT 590: Data Visualization
EGRMGMT 590: Fundamentals of Data Science
EGRMGMT 590: New Opportunities in Big Data