The Leaky Pipeline Problem: Making your Mark as a Woman in Big Data
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The Leaky Pipeline Problem: Making your Mark as a Woman in Big Data Kavitha Mariappan VP of Marketing, Databricks February 8 th , 2017
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Transcript of The Leaky Pipeline Problem: Making your Mark as a Woman in Big Data
The Leaky Pipeline Problem:Making your Mark as a Woman in Big Data
Kavitha Mariappan VP of Marketing, DatabricksFebruary 8th, 2017
About Me
Women are Still Under-Represented in Tech (and Big Data)
SOURCES: 1. U.S. Bureau of Labor Statistics 2. McKinsey and LeanIn.Org Women in the Workplace Report 3. Harvey Nash CIO Survey 2015 4. www/anitaborg.org/
With this rate of progress, it will take until 2133 to close the gender gap,
says the World Economic Forum.
23% of technical jobs in the US are held by women 1
17% of women make it to the C-Suite 2
8% of CIOs in the US are women 3
7% US tech start ups are women-owned 4
Women entrepreneurs begin with of the funding of male-owned ventures1/8 5
Why Does the Gender Gap Still Persist?
The “Network Effect”
Retention due to work-life integration & cultural issues:
the ‘Leaky Pipeline’
Fewer girls are entering STEM
—still!—
The ‘Leaky Pipeline’ IssueWhy?• Lack of female role models• Lack of mentoring opportunities• Work/life challenges• Lack of clear career path• Lack understanding of politics• Perceived lack of skills/experience• Feeling isolated/not supported• Gender stereotyping
Anita Borg Institute 2015 Impact Report
There still is a 50% decline in representation of women from entry to exec levels in tech jobs.
Why are Women in our Field Invisible?
10%of Spark Summit East
Speakersare Women
14%of Spark Summit East
Attendees are Women
at Strata Hadoop San Jose74 of 394
Speakers were Women
Thoughts from Claudia Perlich one of the nation’s top Data Scientists
Ten years ago, having an advanced degree in the equivalent of data science was not exactly sought after in industry, and few of us ventured in that direction
Many women in data science are simply not in the right
places to be seen
Most of her female data science friends have
chosen to stay in academia
Why are Women in our Field Invisible?
The Network Effect• The best way to hire is through referrals!• When it comes to referrals and recommendations,
people tend to recommend others much like themselves, which reproduces the status quo
Sources: 1. Federal Reserve Bank of New York 2. Fernandez & Campero, 2012
64%of employees recommend candidates of the same gender 1
for exec high-tech jobs, referred candidates are much more likely to be men than women 2
The Unconsciously Biased Address Book – The 20% Problem by Rick Klau, Partner at Google Ventures
The Network Effect
Over 1,900 contacts in his address book
399 were women
The previous year 79.7% of people he followed on Twitter were men;today his address book is 79.9% men
Examples of Innate Behavior • We feel uncomfortable to ask for a pay raise or a bonus• We are less likely to self-promote• We opt out even before we throw our hat in the ring• We sit at the table but often don’t ‘take a seat at the table’• We often don’t put our hand up for the high-visibility
projects or promotions
Embrace Adversity with Diversity• In general, I find that playing the gender card is not fair to
either men or women – so let’s be constructive.• Be proactive – ask for what you deserve• You can’t win if you don’t play – seek opportunities and make
them yours• Seek out mentors and networks• Don’t just be the utility technical player • Embrace your ‘inner girl’ • Stay hungry!
As Margaret Thatcher once said, “plan your work for today and every day, then work your plan.”
