A Q&A with Sara Moore, Technical Director Data Science
Cornerstone AI is publishing a series of Q&As with team members to provide more information and context on their role at Cornerstone AI, as well as their professional background. This is the third post of the series. Visit our blog to see previous posts in the series.
Your background is in research and, later, data science - can you tell me a little about why you chose to go into that field in the first place?
Well, data science didn't exist as such when I graduated and was looking for a career. Research was a place where I felt like I could work on interesting problems and have the freedom to explore and think hard about things, and to try to come up with interesting solutions. My undergrad work was in computer science and psychology, which, at the time, felt pretty different from one another, but when I graduated the natural fit was to go somewhere where I could use them both. And I felt like that was research. Since then, I’ve realized that both interests were rooted in a desire to understand how things tick. Whether that was people, or computers, or something else, I like to really get down in the details of why something's happening, and that process makes it easier for me to approach the problem and the solution.
A coworker encouraged me to go into statistics or something quantitative for graduate work, and that eventually led me to biostatistics. But data science, in my experience, is a much more concrete version of statistics. You get to play with data, as in real data and real problems, and not be in the abstract. It’s also interdisciplinary in that you’re working with both the subject matter, whether it’s healthcare or whatever else, and you’re working with something that's a little more agnostic to subject matter, like data. And it's fun because we're never going to run out of data – so there are always going to be more problems to solve.
You worked with Genentech, Lumos Labs, and Project Rōnin before coming to Cornerstone AI – was there anything in particular that compelled you to make this change?
It's funny – the order that those companies are in. At Genentech, I did a summer internship and also some contracting during my grad work. It's a very big pharma company with many buildings, an entire campus, lots and lots of people. Lumos Labs was my first full-time job out of grad school, with a hundred people or so. When I started at Rōnin, it was 35 people or so. And then when I started at Cornerstone, I was employee number six. So in retrospect, that progression toward a smaller and smaller company was a search for a small group of people – finding that team where we can be lean and fast and really get stuff done. That is so motivating. To be able to have an idea one day and implement it the next is huge. And I think at bigger companies, unfortunately, sometimes that gets lost or there’s some accumulation of things that need to be worked on and the new things have to wait. It feels similar to renovating an older house versus building a new one. Building something new is typically easier and more fun, and fewer mistakes can happen. The complexities of renovating and retrofitting is the kind of baggage I feel like can come with an older or bigger company.
In addition to that, Cornerstone had a problem worth solving: a real problem that I had experienced as a data scientist, even before I called myself a data scientist, and it was clear to me that there were people who could benefit from this solution. And I believe in what we're building. I believe it's a good solution to the problem. On top of that, Cornerstone is a place where I can come every day and things keep me interested – the problems that we have keep me engaged. I'm not working on the same thing every day or working on things that I'm not choosing to work on, in the way that I might be at other places.
On a day-to-day basis, what does your work look like? What drives you to continue the work each day?
It is different, really, every day. I work on a lot of different pieces of software that power the back end of our product – the pieces that come together behind the scenes to power Cornerstone’s UI. I’m not necessarily an expert on all of them, but I am pretty good at seeing the connections between them, so I can work well on projects that have a lot of components in different places and figure out how those fit together, how the puzzle comes together. I often am working on challenging bugs or weird things that happen, and figuring out what the cause is because, first of all, it's fun. I’m not sure that everybody thinks that’s so fun, so I'm happy to pick that up. And second, because that knowledge of how things are connected really comes in handy there because sometimes a bug is three different things not talking to each other well. A lot of what I do is writing or documenting code, and communicating and coordinating with other team members about what's going on – a lot of behind-the-scenes work.
What does the future hold for Cornerstone AI?
For one, Cornerstone is going to make the process and this problem of cleaning dirty data easier and easier. I think Cornerstone’s software will become more automated, more hands-off. It will become more useful to people who don't have data science training. I think we can make it easier to use and also better at finding the problems, correcting the problems, and delivering clean data to folks so they can continue working.
The bigger thing that I'm really excited about is the amount of insight we can give customers into their own data. As someone working with data, especially as the size of the dataset grows, you can't go in and look at every single data point; it's just not possible. And even if you can, you can't necessarily come up with a cohesive view from all the different angles over so many dimensions – you need help with that, and there are lots of ways to do that, but I think that Cornerstone has a really good start on it.
If you have vision that isn't 20/20, and then you put on your glasses, things go from being fuzzy or unclear – like maybe the words aren't clear on the page – to being clear, instantly. In the same way, Cornerstone could be the corrective lenses or LASIK for people looking at their data. Cornerstone can provide a lot more clarity to people about what’s going on in their data – the important aspects that they need to pay attention to and deal with before they use it. That's what I'm excited about.
What are you most proud of in your professional and/or personal life?
I grew up in a rural area of North Carolina, and for whatever reason, Berkeley and California became a big dream for me. It wasn't really feasible for me to go out there as an undergrad, but I did for grad school. I'm really proud of that personally and professionally. Had I not moved to the Bay Area, I would not have had the same opportunities – I wouldn't have even known they existed. I wouldn't have met the people I have that led me to work at Cornerstone with this great team. So I’m really proud of that and also grateful for the opportunity.
What are you passionate about outside of work?
I really enjoy getting outside, and I especially enjoy hiking. After moving to California, going to Yosemite became like a pilgrimage, a trip we’d make time for almost every year, and I just went back in June. I love the trails there and was proud to have hiked Half Dome on one of those trips.
And I have a new puppy – she's our first puppy and it's been a big adventure. It's amazing how much their brains can absorb when they're young, so it’s been really fun to be able to teach her lots of things. So yeah, I’m just enjoying hanging out with her and getting outside more with her.