A Q&A with Clara Oromendia, Co-founder & VP Data Science & Product Strategy

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 statistics and biostatistics. Can you tell me a little about why you chose to go into this field in the first place?

I'm a relatively rare breed these days that has been doing stats from the very beginning. I loved the idea of taking numbers and creating information. Biostatistics was something I discovered in college that added humanity to statistics. One of the wonderful things about statistics is that it can be applied to many different areas, and biostatistics focuses especially on humans. Humans are complex, and they're fun. I really enjoyed that biostatistics was very technical and also very human at the same time.

You are one of Cornerstone AI's cofounders. What inspired you to take your career in this direction?

The crux for me was seeing the same problem show up again and again. One of my driving principles professionally and personally is efficiency. From my first job at Weill Cornell, I saw that so much of our time was spent preparing for analysis, and that preparation was mostly the same each time. In graduate school, I had spent a lot of time learning methods to extract the most information from a clean dataset. And then I went into the real world, outside of simulated datasets, and realized that most of the time is spent in this early phase. And most of the gains, especially in healthcare, are in setting yourself up for that analysis as best as possible. 

I started creating pipelines for myself and my team to speed up that process, but then I realized that the issue wasn't just for me, it wasn't just for my team, and it wasn't just in one area of healthcare. 

After Cornell, I worked for several years at a decision support oncology startup. I thought, maybe they've got it figured out there in the health tech world. When I got there, I realized that there was actually an even bigger problem. The data access problem has been largely solved, but we’re still stuck in the same situation of spending so much of our time preparing for the analysis. The actual model building is what data scientists and statisticians think we're going to do most of the time, but it actually is a small percentage of the time. That’s the dirty little secret of data science, and it not only leads to great inefficiency, but also job dissatisfaction. 

Cornerstone’s vision of solving the core of a problem for everyone is the most efficient way to do this. That's really what drives me. As a company that is independent from data sources and applications, Cornerstone can uniquely focus on this problem. Data quality and data preparation is what we do through and through, and that means we can create software and resources that are optimized for that purpose.

Essentially, it was the pull to have this problem solved in the industry that really pushed me to join the party. 

On a day-to-day basis, what does your work look like? What drives you to continue the work each day?

A lot of what I do is helping translate between what software can do and how our customer is doing things today. My background in applied research and tech is very useful when asking customers how they solve this data quality problem today and in explaining how they can do it better and faster with our Cornerstone solution. That’s a combination of many things: from working with customers during demos and introductory conversations all the way to implementation of our software and showing them how to extract value from it. 

I also spend time helping our team internally continue developing the software in ways that solve real problems. That entails thinking about our product as a whole and making sure that the pieces that we're building work together to solve the data quality problem fully.

What does the future hold for Cornerstone AI? 

The concept of data quality is often talked about, but very seldom is it defined precisely. In healthcare, we all want high quality data, but what that means depends a lot on what you're going to use the data for and what else is available to solve that problem. One of the unique opportunities that Cornerstone has is to become an industry standard for measuring data quality and achieving higher levels of data quality. 

Cornerstone is not a data provider, and thus can be an impartial party in quality reporting. We have a vision of having every dataset which is available for analysis also having a data quality report that shows relevant data quality characteristics. As the consumer, you could add more context under which you’d like to use the data, and have information tailored to adjudicate quickly whether that dataset is fit for your specific purpose. Maybe you are looking to license a dataset, or maybe you already have it in-house, figuratively sitting on a shelf. Now that shelf is easy to browse, and rather than having to spend several months to create an understanding of what is in the dataset and only then be able to use it, the succinct information to decide whether it will help answer the question at hand is readily available. Part of the reason many of us have a stack of books on our nightstands waiting to be read is the uncertainty of the gain after the time spent reading it. As the number of RWE datasets licensed grows, organizations have a similar stack of datasets blocked by the upstart energy needed to understand the potential impact. Cornerstone reduces that initial energy and time required, and therefore gets data off the shelf and into scientific analyses.

I see Cornerstone’s future as solving not only individual data quality concerns of datasets, but also as becoming the industry standard for measuring data quality, both as data is coming in and also after it's been processed by and enhanced by Cornerstone algorithms.

What are you most proud of in your professional and/or personal life?

I'm most proud of the team that we've built and the intentionality with which we live at Cornerstone. We started thinking very early on about what kind of culture we wanted to have at Cornerstone. We wanted to make sure that we ask folks to join who want to not only build amazing software and tackle a hard problem, but who also want to do that in a way that makes them want to go to work every day. It’s incredibly rewarding to see this with each individual and the collective force we've created. 

For example, we've been working with a learning and development coach on all sorts of different topics, and we just did a session on healthy conflict. It's wonderful to see the trust that we have in each other, the high expectations we have of each other, and the joy we get from each of us leveling up in our own individual ways and as a company. That makes me really happy, especially because it's a hard thing to do for a group of mostly technical folks, who are not the usual advocates for these programs. We like numbers, we like very concrete things, and yet we want to be able to value that just as much as the human and the team aspect. And this is a really challenging thing to do. 

Outside of that, I’m pleased to remain open to the ways my career has evolved and continues to evolve. . Going back to the question at the beginning of, “Where did you see your career going?” What I saw was continuing to learn, and that's hard, but it's also fun. I'm proud to continue pushing myself to constantly be on the edge of my comfort zone and expand my skills. 

What are you passionate about outside of work?

I really like performance art, and especially live theater. Whether it’s music or art or theater, seeing what humans decide to create is amazing. And the live setting brings in an adrenaline rush that is unmatched in our async life. Very recently decided to join in the fun and started acting in a local theater – it has definitely been rewarding and thrilling!