engineering recruiting today
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Engineering Recruiting Today!Daniel Portillo, VP of Talent, Greylock Partners!
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Perspectives Of an early-stage startup guy
LinkedIn User #47,201 Rypple Customer #1
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Talent shortage
Fine Print Job postings and organic w e b s i t e t r a f f i c i s n o t something I've focused on o v e r t h e y e a r s . S o m e companies rely heavily on them for candidates. I don’t judge if that's how you do things. I prefer going out and getting who we want. I believe it’s impossible to build a great company a n o t h e r o t h e r w a y . Disclosure: We're investors in LinkedIn & Treehouse.
TRENDS
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spray & pray doesn’t work trend is operational & data driven
to find the fish, be strategic & leverage the web
pool is small, but new ways of growing it
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Recruiting is becoming more operational…
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…& data driven
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Basic Metrics
100% (X)
10% to 20%
0.7% to 2%
0.3% to 2%
Total Out reach (Top of funnel) Avg Response Rate: 10-20%
Intro to Offer Rate: 10-15:1
Acceptance Rate: 40-100%
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Real Example
1,450 !
320 (22%)!!
435!
29 (15:1)!
17 (59%)!!
Greylock Talent Team Outreach in Q1
Response rate
Total Introductions
Intro to Offers
Acceptance Rate
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Levers
Top of the funnel
Response Rate
Intro to Offer Rate
Acceptance Rate
Increase outreach using github, linkedin, etc.
AB testing outreach
Debrief after interviews to improve conversion
Pre-closing
FINDING THE FISH
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Don’t bring a knife to a gun-fight
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Essential recruiting tools
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To recruit well & fast, match intent to relevant ability
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How to (scalably) match intent & relevance
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Best sourcer: high relevant, high intent Re
levan
cy
Intent
Scraping Spamming
“Pu
ll Sou
rcin
g”
“Push sourcing”
Job boards
Agencies (do not scale well)
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Matching algorithm It’s a data game
Matching Tags (relevancy)
Extracted tags from candidates &
companies profiles and other sources available.
Behavior (intent)
Convert actions taken on Whitetruffle by companies & candidates to
knowledge to improve matching.
Matching score
Match is released
Human validation
GIT WITH THE TIMES
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Reading github profiles can be tricky
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Dive into the implicit Web
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~10 chars ~500 chars ~1k chars
Explicit Professional Data
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~250k chars ~80k chars ~100k chars
Implicit Data from the web
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Extract professional activity
Analyze & surface skills
Aggregate all contact info
TalentBin’s 360 view *
* he’s happy because he never updates LinkedIn, but now, with TalentBin, you can find him!
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Get…
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Job Posting 2.0
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Grow the pool
© Random House
Education is being disrupted
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Higher education is broken with increasingly higher costs for students and society at larger. Education is no longer a one-time event but a lifelong experience. What is taught in universities is a mismatch with what employers need, especially in technical fields.
Sebastian Thrun Udacity Founder. Google Fellow. Stanford University Comp. Sci. Research Professor. Autonomous Car Inventor. 50 Smartest People in Tech (Fortune). Education disruptor.
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Big breakthroughs happen when wha t ’s s udden l y poss ib le meet s what ’s despera te l y necessa ry. H i g h e r e d u c a t i o n i s prohibitively expensive. But web technologies now allow 100,000+ students to be taught by one Stanford professor.
Daphne Koller Coursera Co-Founder. 3rd generation Ph.D. Stanford University Professor. MacArthur Fellowship winner. Education disruptor.
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To Recap… trend is operational & data driven
There are new amazing tools, but there are no shortcuts
We can help create bigger and better pools of talent
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Thank you
George!
