Across the globe, more than 7.2MM professionals make their living by working in a software engineering capacity - and the United States is home to about ¼ of that population. In this report, we leverage profile, engagement, survey and labor market data to help you learn what makes these professionals tick - and ultimately, how to hire the best for your organization

1. Guide to Tech Talent – United States
April 2017

2. 2
 Demographic overview
 Behavior and engagement
 Market demand and compensation
 Networking habits
 Methodology
Table of contents
About this report
Across the globe, more than 7.2MM professionals make
their living by working in a software engineering
capacity—andthe United States is home to about ¼ of
that population. In this report, we leverage profile,
engagement,survey and labor market data to help you
learn what makes these professionals tick—and
ultimately, how to hire the best for your organization.
7.2MM+ softwareengineersglobally
1.8MM+ in the UnitedStates
238k+ U.S.softwareengineerschangedjobsin 2016
Introduction
Introduction

3. 40K
49K
60K
63K
71K
74K
76K
83K
150K
218K
Data reflects the United States SWE talent pool as of March 2017. Size of dot corresponds to size of regional talent pool. Top 40 regions by talent supplyonly.
Demographicoverview
TalentSupply& MarketDemandby Region
Know your tech hiring hubs: In the map above, “High Demand” regions are those with a large talent supply
and high demand from the market. We call large markets with lower demand “Hidden Gems.” Markets where the talent
supply is small but demand is high are considered “Saturated,” and small, low-demand markets are “SmallMarkets.”
The San Francisco Bay Area boasts both the largest supply of and highest demand for software engineers in the United
States. Seattle is #2 when it comes to demand, followed closely by NYC and Boston. Los Angeles, Dallas/Fort Worth and
Philadelphia are top-10 markets in terms of volume—but feature relatively low demand.
Top Regionsby TalentSupply
3
Talent Pool Overview:
1.8MM+ software engineers in the United States
SF Bay Area
NYC
Seattle
Boston
Washington, D.C.
Los Angeles
Chicago
Dallas/Fort Worth
Atlanta
Philadelphia

4. Software Engineering Specialties & Differentiating Job Titles
4
Front-End Infrastructure&
Cloud
Embedded&
Application
MachineLearning &
DataScience
Mobile Test& Quality
Assurance
See methodology section for additional detail.
Demographicoverview
Embedded Software
Engineer, Firmware
Engineer, Principal
Engineer
Web Developer, CSS,
Web Application
Developer, Front End
Developer
DBA, Systems
Analyst, Data
Architect, Cloud
Architect
Data Scientist,
Hadoop Developer,
Machine Learning
Engineer, Big Data
Architect
iOS Developer, Android
Developer, Game
Designer, Mobile
Application Developer
Test Engineer,
QA Tester,
Cyber Security,
Hacker

5. 5
Front-End Infrastructure & CloudEmbedded& Application
Data reflects the United States SWE talent pool as of March 2017. We can infer a specialtyfor 65% of software engineers in the U.S.. We can infer a gender for 77% of specialized softwareengineers.
MachineLearning & DataScience Test & QualityAssuranceMobile
220k+
members
226k+
members
56k+
members
58k+
members
463k+
members
175k+
members
16%
23% 25%
20% 19%
29%
% Female
% Female % Female
% Female% Female
% Female
1% 7%
15% 21%
56%
0-2 3-5 6-9 10-14 15+
Years of Experience
2% 9%
20% 25%
44%
0-2 3-5 6-9 10-14 15+
Years of Experience
3%
12%
23% 26%
37%
0-2 3-5 6-9 10-14 15+
Years of Experience
1% 6%
15%
24%
53%
0-2 3-5 6-9 10-14 15+
Years of Experience
3%
11%
22% 27%
37%
0-2 3-5 6-9 10-14 15+
Years of Experience
3%
14%
27% 27% 30%
0-2 3-5 6-9 10-14 15+
Years of Experience
Demographicoverview
Top Differentiating Skills Top Differentiating SkillsTop Differentiating Skills
Top Differentiating Skills Top Differentiating Skills Top Differentiating Skills
• Embedded Systems
• C
• Embedded Software
• Debugging
• Linux
• Testing
• JavaScript
• HTML
• XML
• CSS
• jQuery
• SQL
• Business Intel.
• Data Warehousing
• Req. Analysis
• SDLC
• Integration
• Databases
• Machine Learning
• Python
• Algorithms
• Hadoop
• Java
• C++
• Mobile Applications
• Java
• Android
• C++
• JavaScript
• Objective – C
• Testing
• QA
• Test Planning
• Test Automation
• Regression Testing
• Req. Analysis
Most gender-
diverse
specialty
Specialtywith the most
experiencedmembers
Specialization Overview:
Talent pool size, skill sets, experience levels and gender diversity

6. 6
Front-End Infrastructure & CloudEmbedded& Application
Data reflects the United States SWE talent pool as of March 2017. We can infer a specialtyfor 65% of software engineers in the U.S.. Date range for turnover & InMail acceptance = Jan. – Dec. 2016.
MachineLearning & DataScience Test & QualityAssuranceMobile
Demographicoverview
Top Employers Top EmployersTop Employers
Top Employers Top Employers Top Employers
Most concentrated cities
for this talent pool
Hartford, CT – (21%)
San Antonio, TX – (19%)
Most concentrated cities
for this talent pool
Salt Lake City, UT (47%)
Miami, FL – (45%)
Most concentrated cities
for this talent pool
Sacramento, CA – (9%)
San Diego, CA – (9%)
Most concentrated cities
for this talent pool
San Francisco, CA – (10%)
Seattle, WA – (9%)
Most concentrated cities
for this talent pool
San Francisco, CA – (26%)
Los Angeles, CA – (26%)
Most concentrated cities
for this talent pool
Norfolk, VA – (29%)
Baltimore, MD – (24%)
+7% more
receptive to InMail than
the U.S. software
developer average
-7% less
receptive to InMail than
the U.S. software
developer average
+5% more
receptive to InMail than
the U.S. software
developer average
+15% more
receptive to InMail than
the U.S. software
developer average
+0% more
receptive to InMail than
the U.S. software
developer average
+22% more
receptive to InMail than
the U.S. software
developer average
13% 22% 14%
32%
24% 16%
% Turnover
% Turnover % Turnover
% Turnover% Turnover
% Turnover
Most
responsive
to Recruiters
Specialtywith
the highest
turnover
Specialization Overview:
Top employers, regional hubs, receptiveness to outreach and turnover

7. 7
Front-End Infrastructure & CloudEmbedded& Application
Data reflects the United States SWE talent pool as of March 2017. We can infer a specialtyfor 65% of software engineers in the U.S..
MachineLearning & DataScience Test & QualityAssuranceMobile
Demographicoverview
Specialization Overview:
Top schools and fields of study
Top Schools Top SchoolsTop Schools
Top Schools Top Schools Top Schools
Top Fieldsof Study Top Fieldsof StudyTop Fieldsof Study
Top Fieldsof Study Top Fieldsof Study Top Fieldsof Study
0.6K
0.6K
0.6K
0.7K
0.7K
Arizona State
San Jose State
UT Austin
Purdue
University
Georgia Institute
of Tech
3K
3K
8K
10K
16K
Information
Science and Tech
Electronics
Computer
Engineering
Electrical
Engineering
Computer
Science
3.0K
3.3K
3.7K
4.0K
6.0K
Georgia Institute
of Tech
UT Austin
UC Berkeley
University of
Washington
Jawaharlal
Nehru Tech
17K
20K
21K
47K
158K
Electrical
Engineering
Computer
Engineering
Software
Engineering
Information
Science and Tech
Computer
Science
1.2K
1.2K
1.5K
1.6K
2.2K
UC Berkeley
University of
Washington
Osmania
University
University of
Phoenix
Jawaharlal
Nehru Tech
5K
7K
8K
20K
50K
Mathematics
Computer
Engineering
Electrical
Engineering
Information
Science and Tech
Computer
Science
0.9K
1.1K
1.4K
1.4K
1.5K
University of
Washington
Georgia Institute
of Tech
UC Berkeley
Carnegie Mellon
Stanford
University
4K
4K
4K
5K
25K
Mathematics
Computer
Engineering
Electrical
Engineering
Information
Science and Tech
Computer
Science
2.1K
2.2K
2.2K
2.4K
2.6K
San Jose State
Georgia Institute
of Tech
USC
University of
Washington
UC Berkeley
10K
11K
12K
17K
76K
Electrical
Engineering
Software
Engineering
Computer
Engineering
Information
Science and Tech
Computer
Science
1.3K
1.3K
1.7K
1.9K
2.0K
Osmania
University
University of
Washington
San Jose State
Jawaharlal
Nehru Tech
University of
Phoenix
7K
7K
14K
17K
40K
Computer
Engineering
Electronics
Electrical
Engineering
Information
Science and Tech
Computer
Science

8. Software engineers engage by following companies on
LinkedIn—especially those in technology and publishing
8
9
Google
Microsoft
Apple
Amazon
Oracle
IBM
HP
TED Conferences
Facebook
TechCrunch
HP Enterprise
Harvard Business Review
Forbes Magazine
Cisco
Intel
MostFollowedCompanies
(excluding current and former employers)
Data reflects the United States SWE talent pool as of March 2017. All follower numbers shown exclude current and former employers.LinkedInitself removed from follower analysis.
In 2016, TEDConferences,
TechCrunchand Forbes
gained the most U.S. software
engineering followers.
Oracle,Facebook,Tech
Crunch,HPE,Ciscoand Intel
are Top-15 in terms of non-
employee followers for tech
professionals—but not for the
United States in general.
72%
of software engineers follow
at least one company where
they’ve never worked
Behaviorand engagement
These members follow
an average of
companies on LinkedIn

9. Compared to the global population, U.S. software engineers
are engaging more frequently in passive job search activities
Which of the followingactivities have you participated in during the pastmonth?
15%
18%
23%
35%
35%
35%
38%
45%
45%
48%
Reached out to a recruiter or search agency
Applied to a job opportunity that interested me
Interviewed for a job opportunity that interested
me
Networked for professional purposes
Responded to a message from a recruiter about
a new job opportunity
Researched companies that interested me
Updated my resume
Updated my professional profile on LinkedIn
Researched job opportunities that interested me
Learned a new skill
Top Activities – U.S. SoftwareEngineers
2%
-13%
6%
-1%
12%
4%
-2%
13%
7%
12%
Compared to the globalpopulation
Behaviorand engagement 9
Data reflects the United States SWE talent pool as of March 2017. Source:LinkedIn’s 2016 Talent Trends Survey of 26k members across the globe. U.S. SWE sample size = 40.
Whatis passivejob search?
Engineers are more likely to keep
their profile updated and respond
to direct outreach from Recruiters
than the global average—but less
likely to apply to jobs on their own.

10. 432k+ software engineers changed jobs in the past two
years—including regional, sector and role-level moves
10Behaviorand engagement
Tech - Hardware > Tech Software
Tech - Software > Healthcare
Tech - Software > Public Sector
Retail > Tech - Software
Healthcare > Tech - Software
Tech - Software > ProfServ
Tech - Software > FinServ
FinServ > Tech - Software
ProfServ > Tech - Software
Public Sector > Tech - Software
Top Pathsfor those that
ChangedSectors
Project Manager
Business Analyst
Creative Designer
Technology Manager
IT Support Specialist
Consultant
Engineer
IT Consultant
Research Fellow
Student
Top PriorRolesfor thosethat
BecameSoftwareEngineers
NYC > Boston
Pittsburgh > SF Bay Area
Chicago > SF Bay Area
San Diego > SF Bay Area
SF Bay Area > Los Angeles
SF Bay Area > NYC
SF Bay Area > Seattle
Boston > SF Bay Area
Seattle > SF Bay Area
Los Angeles > SF Bay Area
NYC > SF Bay Area
Top Pathsfor those that
ChangedRegions
Data reflects the United States SWE talent pool as of March 2017. Date range = Jan. 2015 – Dec. 2016.
Embedded&
Application:
MachineLearning
& DataScience:
Test& Quality
Assurance:
Infrastructure&
Cloud:
Mobile: Front-End:
While most sector paths
lead to software
companies,Financeand
ProfessionalServices
firms are pulling some
talent away from tech.
Students, research
fellows and other
educationprofessionals
comprisethe bulk of
pre-softwareengineer
talent.
While the SF BayAreais
the clear leader in
terms of engineering
relocation, Seattle,
NYC,L.A.and Boston
have also emerged as
major destinations for
tech talent in the
United States.
Who’sdoingwhat?
The talent pool of MachineLearning& Data
Scienceengineers relocated and changed
sectors most frequently (by percentage).
Front-Endengineers—the largest specialty—
switched jobs in the highest volume.
Total Job Switchersby Specialty
15k (26%) 28k (51%) 54k (24%)45k (26%) 88k (39%) 167k (36%)

11. Machine learning & data science engineers are in the
highest demand from the market
Machine Learning
& Data Science
Mobile
Front-End
Infrastructure &
Cloud
Test & Quality
Assurance
Embedded &
Application
Marketdemandand compensation 11
Data reflects the United States SWE talent pool as of March 2017. Demand calculations include only those members that received at least one InMail in 2016. *Source: LinkedIn’s 2016 Job Switchers survey of 6.7k members across the
globe.North America SWE sample size = 31.
Highv. highestdemand: We estimate market
demand based on the relative volume of job opportunity InMail
outreach to members of a talent pool. And while we’ve called
out differences in demand for key specialties at left, it’s worth
noting that, in 2016, the average U.S. software developer
received 3.2xas much recruiter outreach as the average
LinkedIn member—and that’s only counting members that
received at least one proactive job opportunity message.
MarketDemand
(per member)
TalentSupplyHigh
HighLow
Low
Supply& Demandby Specialty
77%
of software engineers* say they
received a 10% raise or higher upon
changing jobs—compare that to
just 57% for all professionals

12. Marketdemandand compensation 12
Software engineering compensation varies by role and
experience level
Median TotalCompensationby Yearsof ExperienceMedian TotalCompensationby Specialty
Embedded &
Application
MachineLearning
& Data Science
Test & Quality
Assurance
Infrastructure
& Cloud
MobileFront-End 6-15 years 16+ years1-5 years0 years
Machine learning and data science
engineers, who are highly
concentrated in San Franciscoand
Seattle,makethe most money on
average—with those specializingin
embedded &application,
infrastructure & cloud and mobile
developmentfollowing close behind.
Recall:thesespecialties
are the most senior
Predictably,compensation
increases as years of experience
increase—and the biggest jump in
market value happens between a
software engineer’s entry into the
workforceand the five-year mark.
Data reflects the United States SWE talent pool as of March 2017. Source:LinkedIn Salary Explorer.LinkedIn members anonymously volunteer their data, which is then aggregated by geography, role, experienceand industry. Salaries
shown are a weighted average of those aggregations mapped to the software engineering talent pool.Sample sizes vary, though a minimum of 5 actual salaries are included in each aggregation.
$103K
$109K
$116K $116K $118K
$129K
$85K
$105K
$110K
$118KU.S. software engineer
median = $112K

13. Marketdemandand compensation 13
San Francisco and Seattle are home to the highest paid
software engineers
Data reflects the United States SWE talent pool as of March 2017. Size of dot corresponds to size of regional talent pool. Top 20 regions by talent supplyonly. Source: LinkedInSalary Explorer.LinkedIn members anonymously volunteer their
data, which is then aggregated by geography, role, experienceand industry. Salaries shown are a weighted average of those aggregations mapped to the software engineering talent pool. Sample sizes vary, though a minimum of 5 actual
salaries are included in each aggregation.
MedianTotal Compensationby Region
$88k $112k $142k
MedianTotalCompensation
In addition to featuring high pay,
Seattle is the fastest growing
market for software engineers—
with a 7.5% increase in talent
supplyover the past year.
Austin outpaces other
major Texas metro areas
in terms of median
software engineering
compensation.
San Franciscois the #1
U.S. region for each of
three key metrics:
talent supply,market
demand and median
compensation.
Median compensation in
Detroit and Philadelphia
is the lowest of the top-20
U.S. markets.

14. Software engineers are highly interconnected—and frequently
join companies where they know at least one employee
14Networking habits
Data reflects the United States SWE talent pool as of March 2017. Only those software engineers with at least 50 connections are included in this analysis. * Connected at least 30 days beforetheir start date with the company.
The median software engineeris
connectedto 21 other softwareengineers
Of the software engineers that
changedjobs in the past 2 years…
56% moved to
companies where they knew
at leastone employee*
29% moved to
companies where they knew
at leastone otherengineer*
For previously-connected job switchers (56% of
total), the median software engineer was connected
to 2 employees—including one software engineer—
at their new company prior to joining.

15. Methodology
15Methodology
Headline
Professional
description
Jobexperience
summaries
Skills
Jobtitles
1. We startwitha full-profilerole, keywordand skillsetanalysisto
determineoccupational mapping & indicatorsof specialization
2. Once we identifythe in-regiontalentpool of software
engineers,we analyzedemographicdata,career moves
and surveyresponses—aswell as engagementon LinkedIn
withcompaniesandother members.Examples:
Other Notes
• Data captures those LinkedIn members with complete profiles that reflect
holding a current role as a software engineer
• We can infer gender for 77% of U.S. software engineers based on first name
• We can infer a specialty for 65% of U.S. software developers based on
profile keyword search and LinkedIn’s proprietary occupational taxonomy
• Unless otherwise specified, data is updated as of March 2017
Connections
Demandfrom
the market
Formerroles &
career interest
Affinities
Engineeringat LinkedIn
I design and execute user-facing features for the native LinkedIn apps on iOS devices by leveraging mobile
operating system frameworks for multi-threading, persisting data, and managing user experience and graphics
across multiple screen sizes.
Laura Taylor
iOSDeveloper
I’m passionate about building web products that inspire user engagement. As a member of LinkedIn’s mobile engineering
team, I focus on feature development for the native LinkedIn apps.
Senior iOSDeveloper

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