How diversity is driving innovation

In 1971, the U.S. Congress designated August 26 as Women’s Equality Day, when we celebrate women’s right to vote as granted by the 19th Amendment. I believe this is also a day we should celebrate the growing number of women in technology.

As a staff data scientist at Intuit®, I’m proud to work at a diverse and inclusive organization, one that embraces Equal Opportunity. Because of this belief in equity, Intuit is fostering a dynamic environment, which in turn is creating opportunities and driving innovation.

My part in driving innovation at Intuit

Unlike many of my peers, my career as a data scientist began in social sciences. I have a master’s degree in Linguistics, and a Ph.D. in Linguistics with an emphasis in Cognitive Science.

Though I don’t have a math, computer science, and physics background, I believe my degrees and language capabilities have given me some advantages, such as data intuition, knowledge of experimental methods, and, of course, knowledge of NLP methods.

I’ve had the pleasure of working at Intuit for four years. I started as a data scientist and am now a staff data scientist. I’m currently working on transaction categorization for QuickBooks, and spent the last few years focusing on QuickBooks’ self-help space.

I recently led a small team (which I’ll talk about in a moment) that was responsible for creating a machine learning model that recommends the most relevant help article to a QuickBooks user who accessed the help menu before they entered any search terms. The model put us in the running for the Scott Cook Innovation Award, and we won. While we were excited to win, we were also excited that we were tangibly helping users. In fact, it started with the desire to assist users in finding help content faster.

We thought that what the user was doing most recently in the product would be a strong signal for what article they would need (e.g.. if they were clicking around in Invoices form, show them an article about Invoices). Though the simple baseline already in place used this principle, it was only able to effectively use the current page the user was on to make a suggestion. We were able to develop a much more powerful deep learning model that uses the user’s last 20 actions in the product to predict the most relevant help article.

Our model allowed us to more than double the click-through rate on those recommended articles and successfully meet our goal of helping users find relevant content!

Leading a smart, hardworking, and diverse team has been a rewarding experience, even when we shifted to a remote work environment. My manager and team administrator scheduled virtual coffee breaks, team yoga, and happy hours, driving innovation through connection.

Advice for anyone interested in data science and coding

If you’re interested in data science and coding, I have three words: GO FOR IT!

Don’t be intimidated if you find it confusing and difficult at first; keep working at it. After you have the initial basics under your belt, I recommend coming up with a use case of something you’re interested in or want to find out with your skills, then learn what you need to do in order to do it. This will help you focus your learning, reduce what could be an overwhelming experience, and help keep you motivated.

I also highly recommend looking at existing code relevant to your interests on GitHub. This will help you learn what code is like in a real end-to-end use case. You can’t get that from doing tutorials.

Finally, imposter syndrome is real. I still get attacks of it even though I have been working as a data scientist for four years. Realize that this is a normal feeling, and you can feel free to ignore it and keep going. This is a job where there will always be more to learn, and you will never have time to learn everything, so just jump in and enjoy the process.

If you want to hear more from other women who are driving innovation at Intuit, check out what Nimisha Shrivastava, Brinda Sivalingam, and Ramya Kasaraneni all have to say about being Intuit Developers.