The rocket scientist and the actress: There’s no one route to the top jobs
Folks who have nabbed the most SAN FRANCIS CO sought-after jobs in America — high-paying technology roles with a focus on data analysis — range from totally self-taught to elite Ph.Ds. But they all share a common trait: a passion for drawing insights from reams of numbers and statistics. Their backgrounds and the paths they took, from a former actress to baseball-obsessed physics major to an armed services veteran, tell the story of how some Americans have found their way into a market that is booming because of the proliferation of data across industries. CHRIS CHAN, DIRECTOR OF DATA SCIENCE AT FASHION START-UP MM.LAFLEUR
Background: Physics major in college that led to a master’s degree in statistics and a job with the New York Yankees crunching game stats. Pivoted to data science for tech-focused companies, including Yelp and Buzzfeed.
Advice: “Physics backgrounds are very useful because companies now are swirling with trillions of data points.” While some hiring managers question whether boot-camp training is enough, he has had “positive experiences.” Chan cautions that there’s no way to
hide skill deficiencies, “especially at smaller companies where no one has time to hold your hand.”
DAPHNE DORMAN, SENIOR SOFTWARE ENGINEER (DEVOPS) AT VINETI, FORMERLY VITRUVIAN NETWORKS
Background: Former actress, “no college or even advanced math skills.” Taught herself website design and managed the site of a top National Geo
graphic photographer. Contract work for a variety of companies led to her current role.
Advice: Dorman now helps other transgender techies pivot into data-science roles. “For me, interest in the field was enough to push me forward; just asking questions and being curious is literally enough.” She is big on boot camps. “Blogs and tutorials are great, but nothing beats face-to-face instruction.”
THERESA JOHNSON, DATA SCIENTIST, AIRBNB
Background: Has a Ph.D. in aeronautics and astronautics with a focus on plasma physics. Switched to tech after a few Coursera online courses when she realized that her big-data background could be put to use at companies looking for insights from such information.
Advice: “You should come in with a familiarity with statistics and statistical frameworks, and enjoy math as well as science and the art of testing hypotheses. You need deep domain expertise.” She touts Airbnb Connect, a fellowship that runs promising job candidates through a three-month Galvanize boot camp and a six-month Airbnb internship.
ALEX SPENCE, LEAD PRODUCT ENGINEER (DEVOPS) AT SOCIAL MEDIA START-UP SPRINKLR
Background: Served in the armed forces in Iraq as a medic but has “always been very technical.” No college degree but taught himself tech skills by reading articles and books. After the military, he got Microsoft Certification in the Dot-Net framework.
Advice: Find what you need to learn. “Any of the DevOps stuff I’ve been doing, it’s all opensource, there’s so much out there for you to use.” He does think boot camps are a great shortcut, because they force you to learn on your own “and stay focused.”
LESLIE CARR, INFRASTRUCTURE ENGINEERING MANAGER (DEVOPS) AT CLOVER HEALTH
Background: Worked toward a degree in chemical engineering in college but then dropped out and started doing tech support. Amassed enough system administration skills to be hired by a series of top companies, including Google and Twitter.
Advice: As someone who now hires, she’s always looking hard at what tech languages and tools an applicant knows, more than their educational résumé. Desire is key. “You have to want to get into this on your own. It’s not a path people are pushed into.”
GEORGE XING, ANALYTICS MANAGER, LYFT
Background: A college degree in computer science and economics led him to a job on Wall Street analyzing currency fluctuations. Moved to the San Francisco Bay Area and got a job at Indiegogo doing analytics. Now serves as link to various Lyft teams looking for data insights.
Advice: “You need to learn the math and develop the right tech skills in order to have the quantitative ability to do the analysis.” But just as valuable is the ability to translate data findings into English for the less techsavvy in the company. “Curiosity is so key. The best insights come from people who are hungry and curious about finding new insights about this data.”