Sophia Chiang is the VP of Finance + Growth at Xcalar. She has a BS in electrical and computer engineering from Carnegie Mellon and an MBA from MIT. She is a KenKen Jedi and an electric bass Padawan.
In graduate school, I worked one summer at a large hedge fund and my job was to run analysis on dozens of linked spreadsheets with hundreds of thousands of rows of trading data to see how macro events affected investment returns across industries and individual stocks. While I don’t quite remember the results, I do vividly remember how long it took to run analysis on or just navigating through big volumes of data. My love for data continued through to my grad school thesis which was on the predictive factors that determine the performance of biotechnology IPOs over a 30 year period.
So, hindsight being 20-20, I suppose it should have been clear that I was a data junkie and that my career would somehow always include data. As the VP of Finance + Growth at Xcalar, I have the privilege to work with numbers 24x7—from budgeting and forecasting to analyzing the variables that impact our conversion rates.
That sales and communication are as important, if not more important, than technical prowess. As a technical person early on, I always figured my work would speak for itself; I naively believed everyone would be as interested and vested in my work. As my responsibilities have increased both inside and outside of organizations, my role more often than not is to sell/communicate why we do what we do, and why it matters (the narrative), rather than how and what technology was used.
Numbers don’t lie—Wired magazine did a recent post on the continued lack of representation by minority groups (women, black, Hispanic). While data has illuminated the problem, ultimately, increasing diversity will take concrete efforts up and down the chain—from hiring and promoting within organizations to encouraging more minorities to go into CS and engineering majors. I wanted to give a special shout-out to my alma mater, Carnegie Mellon, whose sophomore CS class is 48% women, and overall SCS (school of computer science) female representation is is 30%.
Statistics, statistics, statistics. As an electrical and computer engineer by training, I have always revelled in advanced, theoretical math; often poo-pooing the applied math subjects. I was wrong. I have not done a Fourier transformation in decades, but have been forced to regularly relearn Z-scores, linear regression, and Pareto distribution. It doesn’t matter if you are a rocket scientist, a political campaign manager, or a retail outlet buyer—knowledge of statistics is critical. Analyzing and interpreting data is a superpower in today’s world of data everywhere, everytime, and on everything.
Show up even if you don’t think you have all the checkboxes ticked off. Be confident that you can learn anything quickly; desire and curiosity are far more important that raw knowledge.