How to Hire Data Scientists
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How to Hire Data Scientists
Hirepalooza June 2, 2015
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Director of Partnerships Zipfian Academy
Katie Kent @k80kent
Director, Educational Outcomes Galvanize
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A Perfect Storm of Supply and Demand
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Storage is cheap. And so much cheaper than it used to be.
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Technology
Year Capacity (GB) Cost per GB (USD)
1992 0.08 $3,827.20
1997 2.1 $157.00
2002 80 $3.74
2007 750 $0.35
2012 3,000 $0.05
Source: http://www.jcmit.com/diskprice.htm
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There is more and more data all the time.
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Unprecedented Data Growth
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Data = business value.
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Incredible demand for data scientists stems from a perfect storm of cheap storage, data growth, and recognition
that data = business value.
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The Demand Problem
Source: LinkedIn Analytics
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Traditional educational institutions are not set up to produce industry-ready
data scientists.
The Supply Problem
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‘I look for 3 things in data scientists: math, code, and business
understanding.’
- Hernan Asorey, VP of Product Intelligence at Salesforce
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Data Science Unicorn
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Math & Stats
Computer Science
Domain Expertise
Machine Learning
Software Engineering Research
Unicorn
Data Science
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It’s hard to hire a data scientist.
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3 Lessons from unicorn hunting in the wild.
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Before you start, know what species of data scientist you
need.
1
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“Data scientist” means different things to different people.
Example: A Data Scientist at Facebook is a different species compared to a Data Scientist at Netflix.
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Software Engineering
Data EngineeringMachine Learning
Feature Development
AnalysisTransmission
Visualization & Communication
Project Scoping
Product Analytics
The Data Science Skills Map
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The skills required for a specific role depend on the ultimate deliverables.
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Software Engineering
Data EngineeringMachine Learning
Feature Development
AnalysisTransmission
Visualization & Communication
Project Scoping
Deliver business insights.
Deliver ML prototypes.
Deliver Data Products.
Different skills = different deliverables.
Product Analytics
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Know what species of data scientist you need before you go hunting.
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Know How to Snag Them2
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Great data scientists often have 3 simultaneous offers, so salesmanship
is important.
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Great data scientists want 3 things: interesting data, a strong team, and the opportunity to make an impact.
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Large data sets
What (Great) Data Scientists Want
Interesting Data Strong Team
Different types of data
Opportunity to Make an Impact
Accessible data Mentorship
Collaborators
Opportunity to learn Data is a priority.
Greenfield opportunities.
Creation over optimization.
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Sell what you have. Be smart about what you don’t.
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Auxiliary sources
Maybe your data doesn’t sound like a selling point.
Small Data
Inaccessible dataFix infrastructure
first.
>
>
CHALLENGE SOLUTION
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Training budget
Maybe your team doesn’t sound like a selling point.
No mentorship.
No daily collaborators.
Designate partners.
>
>
CHALLENGE SOLUTION
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Seek an evangelist.
Maybe opportunity for impact isn’t a selling point.
Data not a priority.
Low-hanging fruit are picked.
Seek a researcher to push boundaries.
>
>
CHALLENGE SOLUTION
Optimization is a priority.
Seek an operations researcher.>
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Get In Front of Them
3
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Savvy data science teams share content about their work in places
where data scientists hang out.
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This creates an engine to drive inbound applications.
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‘I get about 300 applications for every posting.’
- Todd Holloway, Data Science Lead at Trulia for 4 years who runs the SF Data Mining Meetup
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Where (Great) Data Scientists Hang Out
Airbnb Nerds
Tech Blogs
Netflix
StitchFix Technology
Tech Talks
Conferences
Data Science Meetups
Channels
DataTau
Competitions
Public Challenges
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Most Active Data Science Meetups
SF Data Mining SF Data ScienceSF Machine
Learning
SF DataKind
http://www.quora.com/What-are-the-best-data-science-big-data-meetups-in-the-San-
Francisco-Bay-AreaLinks and
summaries!
Data Science for Sustainability
Bay Area Women in ML & DS
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Interesting Data Science Conferences
O’Reilly Strata MLConf PyData
DataWeek PAWThe Data Science
Summit
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Great Examples of Tech Blogs
Airbnb NerdsStitchfix
TechnologyNetflix Technology
•nerds.airbnb.com/data/ •http://technology.stitchfix.com/blog/2015/03/31/advice-for-data-scientists/
•http://techblog.netflix.com/
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Public Open Data Challenges
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Data Science Twitter Celebrities
• @hmason - Formerly Accel • @mrogati - VP of Data, Jawbone • @djpatil - Chief Data Scientist, The White House • @peteskomoroch, Formerly Linkedin • @josh_wills, Dir. Data Science, Cloudera • @johnmyleswhite, Co-author of Machine Learning for Hackers
• @hackingdata, Formerly Chief Scientist at Cloudera • @bigdata, Chief Data Scientist at O’Reilly Media
giladlotan.com/2012/11/mapping-twitters-python-data-science-communities/
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Know How to Pick Them
4
*Bonus Lesson!*
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The New Data Science Interview Process
Onsite Interviews
Check for a Pulse
Offer
Take Home Assignment
Less bias, less time, more accurate.
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If you interview data scientists, go read this article:
firstround.com/review/how-to-consistently-hire-remarkable-data-scientists/
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Galvanize Can Help5
*Double Bonus Lesson!*
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Galvanize trains data scientists through immersive educational
programs.
12-week Immersive (fka Zipfian Academy)
GalvanizeU Masters’ Program
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Alumni Employers
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https://dshiringdaysf.eventbrite.com
Hire a Data Scientist from Galvanize
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THANK YOUKATIE KENT| DIRECTOR, EDUCATIONAL OUTCOMES @K80KENT
www.galvanize.com