Diversity and Data – A Q&A with Kshitija (KJ) Gupte

In honor of International Women’s Day, we spent some time getting to know a little more about the one and only Kshitija (KJ) Gupte, Senior Data Scientist and Data Science Lead at Tradeshift. We asked KJ for her take on why women are still underrepresented in data science roles, and why a focus on diversity is so crucial in her particular field.

Can you tell us a little bit about yourself? 

I am originally from Mumbai, India. I did my Bachelor’s in Engineering at Mumbai University and started my career as a mainframes developer for Infosys where I worked for Enterprise clients in Finance and Health Insurance. While Information Management was the primary focus in these years, my learnings have mostly been around the importance of process and planning in data gathering and assimilation. It only enhanced my structural thinking and conceptualization to the point where I was not just an engineer but also a reverse engineer.

I moved to the United States in 2007 as part of an assignment working as a data/business analyst for one of our major clients in Philadelphia – a leading insurance provider.

This move was very pivotal in my career not just as an engineer but as a professional.

Now it was not just my diverse skill set that was gaining momentum, but also diversity in workplace, ethnicities, and backgrounds.

In 2016 after being promoted as a manager in the data analytics practice at PwC where I had been for 4 years, I felt like it was time to segue into a career in data science and become a scientist. With all the immense experience that I had gathered from my past – assimilation of structural, cultural, RDBMS (relational database management systems), and everything in-between “data”, data science felt like the right field to venture into with the growing need for insight-driven data.

What does a typical day look like at work?

The nature of my ‘typical’ day has evolved over the years. Since we are a diverse work culture spread across international time zones, days at Tradeshift start pretty early. Most of the important work, data-driven decisions, and future success roadmaps are hashed out in the early mornings, or that has been my experience at Tradeshift.

I prefer carving out focus periods in my day where I club my meetings together in the early part and use the afternoons to focus on pure coding/technical work for the later part. But that is an ever-changing landscape given the fast-paced nature of our business. I have had to present data and insights to senior leaders oftentimes with just a 10-15 minute lead time where I had to act and look camera ready in the wee hours of the morning and talk data.

But those are the thrilling and challenging moments of a data career. They keep things interesting and exciting.

Why do you think it is important to celebrate International Women’s Day?

Well, I think every day needs to be celebrated as International Women’s Day given the diversity in our industry. We still have a long way to go to give our women their rightful representation and their rightful opportunity in our fast-moving work culture.

Have you faced any barriers in your career due to being a woman? If so, how did you overcome them?

I feel as a woman being a minority in the room was a pattern I have seen ever since my engineering days. The women-to-men ratio was always 1:3 or sometimes even 1:6. As I went higher up in my career ladder it was 1:n. I think this is where the problem is. Representation matters. If there is a lack of women in higher management that oftentimes becomes the culture trickling down to all other teams. It was hard to break through those barriers where I sometimes felt invisible given the gender imbalance.

The only way to overcome such barriers is to step up to the game and not shy away from representing yourself.  If you are the only woman in the room might as well be the most knowledgeable and hence the most empowered one!

Why do you think diversity in the workplace is so important? 

I feel a diverse work culture is the most holistic work culture. It brings empathy just by being from various backgrounds. When you are interacting with people who come from a different culture/race/ethnicity than yours, it increases camaraderie and brings in synergies from all the different cultures, mindsets, ideas, and experiences. It opens borders and brings in more expanded avenues for opportunity and collaboration.

Tying this to data science, we need a lot of intuitive and insightful minds. Problem-solving through data needs one to jump through hoops around biases, critical thinking, and bridging the gap between a practical and analytical approach to things. When we are in a diverse team – gender and cultural – it brings together a mix of all the varied minds to come together and build a more forward-oriented solution.

Data science seems to be quite male-dominated. Why do you think that is, and what could we do to change that?

When you are the only woman in a room full of men, the dynamics change. You don’t want to reinstate the minority any further. So you start disregarding anything and everything remotely feminine. You start acting like a man. Sounding like them, housing their beliefs. Completely disregarding the feminine side of you.

This dynamic discourages more women from joining the troop.

In our race for equality, we have started comparing apples to oranges. The way to change this is to learn to co-exist and be comfortable in our own gender. But this needs efforts from both sides.

I would start by bringing some of our Feminine Energies into engineering to mix with the existing Masculine. Because, clearly, we need more data to draw some clearer insights in that area!

What is the most important piece of advice you have been given?

I once asked one of my favorite mentors – “How do I get my audience to like data and gravitate toward numbers? To really ask relevant questions.”

The answer was empathy. Empathy helps drive motivation. Math helps build trust via concrete numbers. The two when coming together can be a powerful force to lead your audience towards data that won’t just “make sense” but will actually “solve” the real problems of the world.

What women inspire you and why? 

You mean besides my Mother and my Grandmother? (I will talk more about them in my book … keep a look out)!

I have great respect for Indra Nooyi. Her emphasis on staying on top of your own personal skill set and up-levelling based on your own frame of reference is something that inspired me to be where I am today and keep aspiring for newer heights.

KJ, thank you so much for giving us the chance to get to know you a little better. Happy International Women’s Day