For Dataiku's second event of the month, we're happy to bring you a presentation on data science & marketing at Squarespace, followed by a "Speed Data" networking event to get face-to-face time with other data scientists (and maybe even our keynote speaker from Squarespace!)
IMPORTANT: Please RSVP on both the meetup AND the GA website here: https://generalassemb.ly/education/speed-data-marketing-data-science-at-squarespace/new-york-city/71481
Tentative schedule:6:30pm: Pizza + beer7:00pm: Marketing Data Science at Squarespace: The Surprising Effectiveness of Invisible Ads by Braden Purcell, Data Scientist at Squarespace7:30pm: Speed-Data
What is "Speed-data?"Imagine speed-dating, but instead of finding love, you're sharing your love for data science! If you wish to participate, attendees will be paired off after the talk, & will get 10-minute rounds to talk about projects they're working on, questions they have, give/get career advice...etc.. Braden, our keynote speaker from Squarespace, will also be in the mix, & you'll get the chance to get face-time with real, practicing data scientists!
Marketing Data Science at Squarespace: The Surprising Effectiveness of Invisible Ads by Braden Purcell, Data Scientist at Squarespace:Squarespace makes beautiful products to help people with creative ideas succeed. We use many advertising methods to reach consumers that can benefit from our products, but careful analysis is important to determine if these ads truly provide a favorable return on investment. In this talk, I will give a broad overview of marketing data science at Squarespace. I will then dive deeper into a recent project in which we combined experiments, data analysis, & statistical modeling to assess the effectiveness of digital ads. The results highlight how data-driven measurement can dramatically improve marketing decision-making.
Braden is a data scientist on the marketing analytics team at Squarespace where he develops tools & analyses to optimize marketing spending & forecast performance. Before that he was a postdoctoral scientist at the NYU Center for Neural Science where he used computational modeling & neurophysiology to understand how the brain makes decisions. He has a PhD in cognitive neuroscience from Vanderbilt University.