From Stay-at-Home Parent to Data Scientist

Engineering, Technology Screen Shot 2018-10-10 at 6.06.07 PM

When I was pregnant with my second child, the startup I was working for failed and I was out of a job. It was 2002 and the tech bubble had burst. I was far from alone — many startups were failing, and many people were out of a job. So I decided, rather than competing against people who weren’t sporting a “6-months pregnant” belly, I would take a year off and stay home with my kids. My memories of not having a “mother’s room” at the startup and pumping (and being interrupted) in random places — the team kitchen, the bathroom, the conference room — were far too vivid for me to want to repeat the experience. So I thought, sure, for one year I can probably handle being a stay-at-home parent.

While I love being a mom and always wanted to have kids, I never pictured myself as a “career parent.” When I was a kid, and a woman walked by with a baby and a puppy, it was my sister who said, “Look at the cute baby,” while I said “Look at the cute puppy!” And when someone I dated said his ideal wife would have a PhD but would want to stay home with the kids, I thought, “Fat chance of that!” I had worked too hard on getting a PhD to “give it all up.” But one year? Yeah, I could do that.

Six years later… Yup, I loved being a stay-at-home parent. One year turned into two, two into three, and it wasn’t until my youngest was in first grade in 2008 that I finally decided it was time to go back to work. My husband and I had gotten used to the luxury (and in the Bay Area it is definitely a luxury!) of having one parent available to drive the kids to and from school, sports practices, dentist appointments, and playdates. So my plan was to work part-time. But how could I get a part-time job that was interesting enough to make it worthwhile tojuggle home and work responsibilities?

When I first finished my PhD in Operations Research and was looking for a job, I searched for “statistics” or “computer science” to find relevant positions. But something amazing had happened while I was out of the workforce. The vast amount of data that was being collected and needed to be analyzed had resulted in a new appreciation for my kind of technical skills, and data science (although it wasn’t called that yet) was born! There were so many jobs that looked exciting (including some that I could actually find by searching the job board on “operationsresearch” — amazing!). I didn’t want a part-time job anymore — I wanted to work full-time!

But how was I going to get one of these amazing jobs? I had been out of the workforce for six years. And it had been 15 years since I left grad school. I knew I had the right skills for some of these jobs, but I hadn’t used them in a long time. I knew I’d be a little rusty, but I didn’t realize how much I’d forgotten until I started interviewing. (I don’t think I’ll ever forget “homoscedasticity” again! I still can’t say it, but I haven’t forgotten it.)

That is when I learned the real power of a network. My resume got into the right hands because someone referred me. I got an offer of a contract-to-hire position, because someone I used to work with went to bat for me at Intuit. Had I known that my former colleagues would have that big an impact on my re-entry into the workforce, I’d have spent more time nurturing those relationships.

And while I still recommend nurturing your network to anyone who plans to re-enter the workforce after taking a lengthy leave, I’m happy to report that things have become easier. There are now “returnship” programs made for people like me — people who have strong technical skills and need a chance to dust them off and show how much value they can add. Intuit has such a program, called Intuit Again, and we are looking for software engineering or analytics candidates.

So if you have a PhD (or other degree) but wanted to stay home with your kids, if you’re ready to re-enter the workforce, dust off those skills and jump back in. There are programs available to support you!

Diane Chang is a Distinguished Data Scientist at Intuit, where she powers the prosperity of consumers and small businesses with machine learning, behavioral analysis, and risk prediction. Diane initially worked on TurboTax, looking at the effectiveness of our digital marketing campaigns, understanding user behavior in the product, and analyzing how customers get help when they need it. She also helped launch QuickBooks Capital, predicting outcomes for loan applicants. She is currently applying AI/ML techniques to customer care. Diane has a PhD in Operations Research from Stanford. She previously worked for a small mathematical consulting firm, and a start-up in the online advertising space. Prior to joining Intuit, Diane was a stay-at-home mom for 6 years.

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