NetSeer catches up with Mona Mojdeh, Senior Scientist, on the transition from academia to startup life, being a female engineer in Silicon Valley, and what’s ripe for disruption.
What exactly does a data scientist do all day?
We build frameworks that allow us analyze the huge amount of data we collect on a daily basis and enable us to predict the future behavior of our systems.
Sounds complex! So, how did you come to join NetSeer?
I first heard about NetSeer from a good friend of mine and was intrigued by what the company does. After checking out NetSeer and its employees’ backgrounds on LinkedIn it was clear that NetSeer has some very talented people, so it seemed like a great fit. And I was right – I’ve been with NetSeer nearly a year now.
What makes you excited about coming in to work every day?
I have to say that it’s both the people and the projects. I enjoy working with some of the smartest people I know on some of the most challenging projects.
Did you always know you wanted to be an engineer? What inspired you to study computer engineering?
Yes. I remember when I was interviewing for my middle school at the age of 10, I was asked what major I would like to pursue – and my answer was computer engineering! I’m not sure why I was compelled to make that decision at such an early age. But I think what has always fascinated me about computers is the sheer variety of stuff that can be created and harnessed with computing. Although it may sound counterintuitive, I truly believe computers allow humans to be more imaginative.
What surprised you most about making the transition from academia to startup life?
I have to say how fast-paced the startup environment is. The time between when the decision is made to build a system to the time that it is actually deployed and we are already looking into performance optimization can be as short as a month — which is unheard of in academia.
What type of projects are you working on?
I am currently working on a prediction engine project where we look into click/conversion data and predict the future performance for the different campaigns we run. It’s so rewarding to see how some strategic tweaks to the system can result in a boost to the click-through rate of a campaign by as much as thirty percent.
Stating the obvious here, but Silicon Valley isn’t exactly known for gender diversity in tech. How’s life as a female Big Data engineer?
I actually faced this situation previously when I started my Ph.D. studies at the University of Waterloo in Canada, where fewer than ten percent of the grad students were women. There I joined the Women in Computer Science committee trying to promote CS among girls of all different age groups. Since moving to Silicon Valley, I’ve been inspired by Sheryl Sandberg’s Lean In project and am actively involved in creating a like-minded circle by reaching out to other highly motivated, achieving women. I truly believe every little step counts.
In ten years, Big Data will be ______.
Ten years is such a long time in Web industry! If anyone can predict the future of Big Data in ten years they stand to amass well-deserved notoriety, and surely a ton of profit. One sure thing is now everyone has the ability to collect huge amount of data – but the real value is how you extract information from this data. That information is the real source of revenue.
What might someone be surprised to learn about you?
I am actually hugely passionate about all sorts of dancing. From classic to ethnic dancing to my favorite Zumba class, I love the creative expression that dance offers. I’m also very passionate about the fashion world – which happens to be ripe for disruption. It’s all about striking that correct balance between left- and right-brain activities, right?
Thanks Mona, we’re lucky to have you.