Even the titles in tech are innovative. Data Scientist. Whether you think it’s about primarily math or primarily engineering, you’re right. In our conversation with Hilary Mason, the resident Data Scientist at Accel, we learned that being a data scientist includes math, statistics and software engineering skills rolled into one job. She says it’s “three capabilities, math, code and communication in one person”. As a data scientist Mason stresses the importance of being curious about the world and curious about human behavior since so much of data science is learning something about the world that was previously obscured. “You’re learning things through analyzing data about something that you never would’ve understood before”.
Recent innovations in technology have reduced the cost of working with data fueling Mason’s fascination and enjoyment of data science. She says, “ Data scientists today aren’t smarter than the people working with data 30 years ago. 30 years ago the cost was so much greater that it took a huge investment and it served you better to spend that investment in something extremely low risk. Now the technology is so cheap that there’s essentially zero cost to playing with it.”
Her desire to create things quickly that will be used by millions of people the world over has kept Mason in startups. She advises that curiosity and keen eyes are the best ways to determine whether or not a startup will be a good fit: “Look for the way people who work together interact. Look for them to support each other when they’re not together, not to talk about each other behind their backs. Also look for evidence, like, is the fridge full of beer or is it full of healthy snacks? Not that there is anything wrong with beer, but you’re optimizing for an environment that you’re going to like. It’s also helpful to look at people who work there and talk to people who might have a variety of experiences instead of a couple of people who seem fairly homogenous.”
She also discussed the value of diversity and product teams reflecting users, “It is my intuition that whenever you have a diverse set of experiences and you’re working on building a product for a diverse set of people, it’s much easier to have those people in the room… Recently I was in a room discussing the data around a certain path, and I realized that I was in the room with a fairly homogenized group and none of us have the right background or perspective to validate the discussion we are having right now. I was able to say, we need to pause here and bring someone who can actually tell us if this is correct or not. But that was an obvious case of where having that diverse perspective in the room would’ve been really beneficial.”
The best lesson she ever learned was “if you follow all the rules and you do whatever other people tell you you’re supposed to do all the time, trying to please them, you can only ever be mediocre at pleasing people. Mason believes that a lot of curiosity along with the privilege to actually take risks and not be afraid of what happens when things don’t work,” has made the difference in her career. Mason says that, “In order to be the best data scientist, the best computer scientist, the best creative technologist I have to do what I think is most important and do it as well as I can”.