Lisa Burton directs a greenhouse for early stage, women-led startups in media and tech. “Our team finds and invests in companies.”
Her PhD is in Mechanical Engineering focused on data-driven mathematical modeling, which was a natural step toward data science. “When I graduated,” she says, “data science had just started to boom. But when I learned what companies were looking for from data scientists, I quickly realized it was everything I’d loved about my research.”
So, right out of grad school, she became the first data scientist at an adtech startup in Austin. She loved it. She used data to optimize bids in paid search advertising to automate and improve the process. From there, she went to a mobile payments startup, then out on her own as an independent data-science consultant for startups. That’s where she met a client who eventually became her cofounder in a company that used social media data to help brands understand their customers.
She brings all that experience to her current role. “We meet the most incredible founders and companies,” she says. But one thing she learned in her first job has influenced everything since: I learned that being able to communicate data science to a broad audience and get them excited and on board is hugely important. This applies to everything I’ve done since.”
Her most recent read?
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil. “It talks about the potential biases and inequalities that are introduced when creating models,” she says.
In her glass?
Champagne. “Like Napoleon Bonaparte, ‘I drink champagne when I win, to celebrate, and I drink champagne when I lose, to console myself.’”