Spotlight: Leanne Bradley

Our?Spotlight Series?aims to highlight women in different Engineering teams across LinkedIn. Featured writers provide insight into their role and what they do at LinkedIn.

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Spotlight: Leanne Bradley, Data Science Manager, Notifications & Network Growth at LinkedIn

I spent the summer of 1997 working at a chicken abattoir. I was 16 and my family lived in a small town in rural Ontario, close to Justin Bieber’s birthplace. The chicken farm was the only place with job openings so that was the job I had, and maybe it was also the push I needed to venture out.?

When I arrived at the University of Waterloo a few summers later, fewer than 10% of my Math class were female. Many of us had a surprising thing in common - we were using math to escape. We came from unstable homes, and math was stable. It was objective, logical, and as we later learned, also provided economic escape. My friends went on to become ocean scientists and tech leaders, careers none of us envisioned when we started college. For me it was the same - my math degree opened doors to work in Chicago, New York, and San Francisco; ultimately leading me to the sexiest job of the 21st century: Data Scientist.?

The University of Waterloo’s math program was the most competitive in Canada and one thing became clear during my time there: I wasn’t the best. I was good at math, sure, but I wasn’t at the top of my class and would never be a professor. So I had to reevaluate. What was unique about me? I was a math major who worked as a cocktail waitress and aced the LSAT. That was unique - my combination of skills. I may not be the best mathematician or communicator, but I was pretty great when it came to combining the two. That was the unique set that made me special, and that’s what I pursued as I went into the workforce.

I started with financial risk consulting - actuarial and financial analytics. This was before the days of widespread big computing but many core skills align with today’s data science roles: translating business problems into statistical and data-driven analyses, presenting nuanced results to non-technical audiences, and performing root cause analyses.

After 10 years in financial risk analytics, I wanted to play with bigger data. I was particularly interested in member activity data so I applied for the Master of Information and Data Science program at UC Berkeley. This program up-leveled my coding and statistical skills to transfer to Data Science. However, other skills from my time in finance; communication, problem solving and root cause analysis, were all directly transferable to Data Science.?

Breaking into the tech industry was a matter of describing my experience clearly and explaining its applicability during interviews. Although this can be challenging at first when switching industries, it helps to study both industries’ jargon and communicate your experience with terminology that the recruiter and interviewer are familiar with. I landed a Data Science role at LinkedIn in February 2015 and haven’t looked back since. This has easily been the most exciting, challenging, and satisfying work of my life.?

Looking back, all of my combined experiences; whether it be working at the chicken farm, waitressing, or financial consulting have led me to where I am today. I encourage anyone interested in pivoting to Data Science or the tech industry to look at your unique combination of skills and see how they can be most applicable. Your experience is valuable and starting a new career does not have to mean starting from scratch.

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