Burtch Big Data

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The

Study

Salaries for Big Data ProfessionalsJuly 2013

Burtch Works Executive RecruitingLinda Burtch, Managing Director

BurtchWor s


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© 2013, Burtch Works LLC, Reproduction Prohibited THE BURTCH WORKS STUDY 2

TABLE OF CONTENTS

Section 1: Introduction ......................................................................................... 3

Study Objective ................................................................................................................... 4

About Burtch Works ........................................................................................................... 4

Why the Burtch Works Study is Unprecedented ................................................................ 5

Section 2: Study Design ......................................................................................... 6

The Sample ......................................................................................................................... 7

Identifying Big Data Professionals ...................................................................................... 7

Completeness and Age of Data ........................................................................................... 8

Segmentations of Big Data Professionals ........................................................................... 9

Section 3: Big Data Professionals: Who They Are ................................................. 12

Overview ........................................................................................................................... 13

Age of Big Data Professionals ........................................................................................... 14

Gender of Big Data Professionals ..................................................................................... 15Education of Big Data Professionals ................................................................................. 16

Residency Status of Big Data Professionals ...................................................................... 17

Section 4: Big Data Professionals: What They Earn .............................................. 19

Overview ........................................................................................................................... 20

Compensation by Job Level .............................................................................................. 21

Compensation by Education ............................................................................................. 23

Special Report: Compensation for Entry Level Jobs by Education .................................... 26

Compensation by Residency Status .................................................................................. 27

Compensation by Region .................................................................................................. 29

Compensation by Industry ................................................................................................ 32

Compensation by Gender ................................................................................................. 37

Section 5: Special Report: Salary Increases of Big Data Professionals ................... 38

Overview ........................................................................................................................... 39

Base Salary Change by Job Title ........................................................................................ 40

Base Salary Change by Education ..................................................................................... 41

Section 6: Where do we go from here? ................................................................ 42

Recruiting & Retaining Big Data Professionals.................................................................. 43

Section 7: Appendix ............................................................................................ 44Glossary of Terms ............................................................................................................ 45

Burtch Works Executive Recruiting, 1560 Sherman Avenue, Suite 1005, Evanston, IL 60201

847-440-8555 | www.burtchworks.com | [email protected]

Survey design consulting services provided by:

Fred Crandall, Ph.D., Managing Director, Eastwood Group Partners, Ltd.

© 2013, Burtch Works LLC. Unauthorized reproduction is strictly prohibited. Opinions reflect judgment at time of

publication and are subject to change.

http://www.burtchworks.com/http://www.burtchworks.com/http://www.burtchworks.com/mailto:[email protected]:[email protected]:[email protected]:[email protected]://www.burtchworks.com/


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Section 1

INTRODUCTION


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Study Objective

The purpose of this report is to provide up-to-date ifoatio o the opesatio of Big Data

professionals. Big Data pofessioals ae idiiduals ho a appl sophistiated uatitatie skills

to data describing transactions, interactions or other behaviors of people to derive insights and

pesie atios. The ae distiguished fo the uats of the past the shee uatit of

data on which they operate, an abundance made possible by new opportunities for measuring

behaviors (most notably, the opportunity to measure what people do online, but there are many

others, such as those presented by customer loyalty programs) and advances in technologies for the

storage and retrieval of data (for example, Hadoop).

Because the value of Big Data has been demonstrated many times, the demand for Big Data

professionals is growing rapidly. Despite a keen need for current and reliable information about the

compensation of Big Data professionals, no such information has been available. Burtch Works

here takes advantage of data that it has for 2,845 Big Data professionals in the U.S. to report who

they are, how much they earn, and how their pay varies with level of responsibility, years of

experience, education, where they live, and the industry in which they work.

About Burtch Works

Burtch Works Executive Recruiting is a team of recruiters with decades of experience placing

quantitative professionals in the most in-demand jobs on the market. They have long-established

relationships with thousands of professionals who work in various industries to support the recent

influx of information, as well as with hundreds of companies that rely on workers to harness the

power of marketing analytics. Burtch Works is therefore able to provide unparalleled insight into

the hiring and compensation of these professionals and with this report further shed light on a

previously unexplored area of the job market.

Linda Burtch, the Managing Director of Burtch Works, has 30 years of experience recruiting inanalytics and knows the space and the talent thoroughly. She has maintained a blog for many

years, writing on topics of importance to the analytics community. In addition, she maintains a

strong social network presence serving as a conduit for conveying relevant information and follows

influential leaders in the analytics community closely. She has also been a frequent speaker on Big

Data career topics at luncheons, conferences, corporate gatherings and webinars. Linda has been

part of the Executive Board of the Chicago Chapter of the American Statistical Association and is

uetl seig as the Boad’s Pesidet.

Ms. Burtch and her colleagues have strong relationships with over 17,000 quantitative

professionals, many of whom Burtch Works has kept in close touch with throughout their career

statig ith the opletio of thei Maste’s ad Ph.D. pogas. As these idiiduals pogess itheir careers, Burtch Works maintains regular correspondences through phone calls, emails, and

networking events. Through these interactions, Burtch Works has meticulously collected invaluable

ifoatio aout pofessioals’ opesatio ad the fatos that ifluee it suh as thei

education, years of experience and industry of employment.


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The Big Data professionals in this study have worked at more than 700 firms that include large

multinational corporations, start-ups, management consulting firms, advertising agencies, niche

quantitative firms, and research organizations. Burtch Works communicates with the hiring

managers and human resources specialists of such companies who are staffing quantitative roles on

a daily basis, staying abreast of job requirements and hiring practices. This latest report is a

culmination of their findings which they are excited to present to both employers and employees in

the far reaching world of Big Data.

Why the Burtch Works Study is Unprecedented

The Burtch Works Study is different from any other compensation survey because:

This study focuses solely on the compensation of Big Data professionals, and the results

are not confounded with trends in the compensation of other related professionals, such as

web and business intelligence analysts. Burtch Works assiduously excluded data about the

compensation of these other professionals from the data used to derive the results

reported here. Although Burtch Works has relationships with far more quantitative

professionals, compensation data for only 2,845 judged to be Big Data professionals withdeep analytical skills were used for this study.

Burtch Works staff collected the data by interviewing Big Data professionals about their

current jobs. This approach differs from the traditional approach used for salary surveys,

which is to obtain compensation data from human resources departments, who have

difficulty identifying those employees of their firms who fall into this category. This is

eause a fi’s Big Data pofessioals ae tpiall ot i a depatet that is ol fo suh

professionals and, instead, are found in many departments throughout a firm. Moreover,

job titles of Big Data professionals, which vary widely across and even within firms, often do

not make clear that they are Big Data professionals. Another important advantage of the

interview process is that Burtch Works’ staff was able to obtain information about theprofessionals not often provided by human resources departments but with which

compensation often varies, such as education and residency status. Finally, because of their

knowledge of the Big Data profession, when recruiters conducted interviews, they were

able to obtain corrections or clarifications when information provided by the professionals

did not seem credible.

Burtch Works shows how compensation varies by region, industry, education and

residency status. Burtch works developed a categorization of jobs by management

responsibility (whether the job includes a responsibility for managing other employees) and

level (level of management responsibility or depth of expertise) and then assigned each

individual for which it has compensation data to one of these categories. This is typicallydone for compensation surveys. However, because Burtch Works has compensation data

for 2,845 Big Data professionals, there were many individuals assigned to most of these

categories. Consequently, in addition to showing how compensation varies across these

categories, Burtch Works also shows how compensation varies within a category by region,

industry, education and residency status.


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Section 2

STUDY DESIGN


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The Sample

The sample consists of 2,845 of the more than 17,000 quantitative professionals with whom Burtch

Works has relationships. All of these 2,845 professionals have the education, skills and job

responsibilities typical of Big Data professionals. Additionally, for each one, Burtch Works has the

data necessary to show how Big Data professionals are compensated and what their compensation

depends on. Finally, for each professional in the sample, the data available were collected in aninterview done no more than 30 months ago.

Identifying Big Data Professionals

Burtch Works looked at the education, skills and job responsibilities of quantitative professionals to

identify those who are Big Data Professionals.

Firstly, Big Data professionals have a degree – usuall a adaed oe, suh as a Maste’s degee

or Ph.D. – in a quantitative discipline such as Statistics, Applied Mathematics, Operations Research

or Economics. In addition, some professionals with an MBA were also judged to be Big Dataprofessionals if they described their MBA program as one having a quantitative emphasis, which is

often true of graduates of business schools such as those at the Massachusetts Institute of

Technology and Carnegie Mellon University.

Secondly, Big Data professionals generally have skill using one or more tools for operating on Big

Data, such as SAS, R, Hadoop, and SQL.

Thirdly, Burtch Works looked for Big Data professionals with job responsibilities in one of these

areas:

Analytical Database Marketing: Studies existing customers with using methods such ascustomer segmentation, campaign targeting and effectiveness, propensity modeling, and

customer lifetime value analysis.

Analytics Management: Manages analytics projects, usually without being hands-on with

data (might use Excel, but no advanced tools). Sometimes does not have a formal education

in one of the quantitative disciplines in the list above.

Business Intelligence: Specializes in establishing data warehouses and other infrastructure

for accommodating Big Data, and might also have a responsibility for basic analytics and

reporting.

Credit Risk Analytics: Measures consumer, enterprise, and market risk levels. Results of

analyses might impact the price of product, such as the interest rate for a credit card or its

availability, as in the case of a loan.

Data Science: Utilizes proficiency for data management and analytical skills, to make Big

Data accessible and derive useful information from Big Data.


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Marketing Science: Predicts consumer behavior using analytics such as marketing mix

modeling. Analysis can use transaction-, store-, or market-level data.

Operations Research: Finds optimal solutions to problems such as those that often occur in

logistics, manufacturing, inventory management, and revenue yield management using

methods such as linear, integer and network programming.

After consideration of the work done by individuals in Analytics Management, Business Intelligence,and Operations Research jobs, Burtch Works decided to exclude them from the sample. Data

scientists, however, are certainly Big Data professionals, but because this subset of professionals is

so new, and because their compensation is so unlike that of other Big Data Professionals, Burtch

Works decided to exclude them from the sample and will, in the future, publish a separate study for

data scientists.

Completeness and Age of Data

Burtch Works included a professional in the sample only if it has complete data for the professional.

This includes compensation data – base salary, bonus eligibility and last bonus received -- but alsoknowledge of whether a professional manages other people and the number managed, years of

experience, region of the U.S. where the professional lives, industry of employment, education,

residency status, and gender. Burtch Works required all of these data so that it can describe the

current population of Big Data professionals and show how their compensation varies with their

attributes.

Additionally, Burtch Works included a professional in the sample only if the data available for the

professional was obtained in the last 30 months, which is typical of compensation surveys. Each of

the 2,845 professionals in the sample was interviewed by a Burtch Works recruiter at some point

during the 30 months ending May, 2013, most within the last year. Recruiters did these interviews

in the course of executing searches for clients.


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Segmentations of Big Data Professionals

Burtch Works segmented Big Data professionals to investigate how their compensation varies with

demographic attributes of the professionals and characteristics of their jobs. Some of these

segmentations are straightforward, such as segmentations by education, region, industry of

employment, and residency status. However, Burtch Works also divided the professionals into six

categories based on whether a professional manages employees and, if so, the level ofmanagement responsibility, and if not, the depth of expertise:

Individual Contributors

Level ResponsibilityTypical Years

of Experience

Level 1 Learning the job, hands-on analytics and

modeling

0-3 years

Level 2 Hands-on with data, working with more

advanced problems and models, may

help train Analysts

4-8 years

Level 3 Considered an analytics Subject Matter

Expert, mentors and trains analysts

9+ years

Managers

Level ResponsibilityTypical Number

of Reports

Level 1 Tactical manager who leads a smallgroup within a function, responsible for

executing limited projects or tasks within

a project

1-3 reports(direct or matrix)

Level 2 Manager who leads a function and

manages a moderately sized team,

responsible for executing strategy

4-9 reports

(direct or matrix)

Level 3 Member of senior management who

determines strategy and leads large

teams, manages at the executive level

10+ reports

(direct or matrix)

Figure 1. Definition of Individual Contributor Job Levels

Figure 2. Definition of Manager Job Levels


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Burtch Works divided the U.S. into these five categories:

Northeast

Southeast

Midwest

Mountain

West Coast

These regions are defined as Figure 3 shows below:

Figure 3. U.S. Geographic Regions

WEST

COAST

MOUNTAIN MIDWEST

SOUTHEAST

NORTHEAST

Note: The Northeast included areas of Virginia within 50 miles of Washington, DC, and the Midwest included areas ofPennsylvania within 75 miles of Pittsburgh.


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The firms for which professionals work were divided into these nine industries:

Advertising/Marketing Services

Consulting

Consumer Packaged Goods

Financial Services

Healthcare/Pharmaceuticals

Outsourcing

Retail

Tech/Telecom

Other

Each professional was assigned to one of these five residency status categories:

U.S. Citizen

F-1/OPT

H-1B

Permanent Resident Other

Finally, each professional was in one of these five education categories:

No college degree

Bahelo’s degee

Maste’s degee

Ph.D. all-but-dissertation (ABD)

Ph.D.


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Section 3

BIG DATA PROFESSIONALS:

WHO THEY ARE


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Overview

• Big Data professionals are young. Three quarters of them have no more than 15 years of

experience.

• Big Data professionals are overwhelmingly male, particularly those at more senior levels.

• Big Data pofessioals ae highl eduated. % hae at least a Maste’s degee.

• 39% of Big Data professionals are not U.S. citizens. Significantly fewer than half of individual

contributors at levels 1 and 2 are U.S. citizens.


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Age of Big Data Professionals

The recruiters at Burtch Works do not ask the age of the professionals with whom they work.

However, they do ask them for their years of work experience, which is highly correlated with age.

Big Data professionals are likely to be young: the median years of experience is eleven. Three

quarters of Big Data professionals have no more than 15 years of experience.

Figure 4. Big Data Professionals by Years of Experience

0

100

200

300

400

500

600

700

0-5 6-10 11-15 16-20 21-25 26-30 31-35 36-40 40+

N u m b e r o f P r o f e s s i o n a l s

Years of Experience

Median: 11 years


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Gender of Big Data Professionals

As is true of many professions that require an education in a STEM field, there are relatively few

women among Big Data professionals: only 25% are women. The more years of experience a

professional has, the less likely it is that the professional is a woman:

These results are in line with other STEM findings:

Math, Science, and Engineering: e to ee oa i the field1

Computer Science: oe opise -% of the oputig okfoe2

Science, Technology, Engineering and Math: women occupy less than a quarter of the

STEM positions3

1 Women affected by male to female ratio in math, science and engineering settings. Association for Psychological Science.

http://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-

and-engineering-settings.html 2 Women in computing. http://en.wikipedia.org/wiki/Women_in_computing

3 The STEM gender gap. Decisions Based on Evidence. http://www.decisionsonevidence.com/2013/04/the-stem-gender-gap/

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0-5

6-10

11-15

16-20

21-25

26-30

31-35

36-40

40+

Y e a r s

' E x p e r i e n c e

Male Female

Figure 5. Gender of Big Data Professionals by Years of Experience

http://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-and-engineering-settings.htmlhttp://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-and-engineering-settings.htmlhttp://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-and-engineering-settings.htmlhttp://en.wikipedia.org/wiki/Women_in_computinghttp://en.wikipedia.org/wiki/Women_in_computinghttp://en.wikipedia.org/wiki/Women_in_computinghttp://www.decisionsonevidence.com/2013/04/the-stem-gender-gap/http://www.decisionsonevidence.com/2013/04/the-stem-gender-gap/http://www.decisionsonevidence.com/2013/04/the-stem-gender-gap/http://www.decisionsonevidence.com/2013/04/the-stem-gender-gap/http://en.wikipedia.org/wiki/Women_in_computinghttp://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-and-engineering-settings.htmlhttp://www.psychologicalscience.org/index.php/news/releases/women-affected-by-male-to-female-ratio-in-math-science-and-engineering-settings.html


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Education of Big Data Professionals

Big Data professionals are also highly educated: 86% have an advanced degree.

Figure 6. Big Data Professionals by Education

Bachelor's

13%

Master's

64%

PhD, ABD

2%

PhD

20%

No Degree

1%


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Will not

transfer

27%

Will transfer67%

Will transfer

exceptionaltalent

6%

All Industries 22%

70%

8%

Consulting/Advertising

42%

50%

8%

Retail

23%

77%

Corporate (non-retail)

Because so many of the individuals with the best training and experience to be Big Data

professionals are from abroad, most companies employing these professionals are willing to

sponsor applications to obtain or transfer visas:

Figure 9. Firms Employing Big Data Professionals by Willingness to Sponsor Visa Applications or Transfers


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Section 4

BIG DATA PROFESSIONALS:

WHAT THEY EARN


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Overview

• Salaries and bonuses are greater for managers than for individual contributors, and they

increase significantly with level.

• Among individual contributors and the most junior managers, salaries vary with education

completed.

• Education particularly influences salaries of Big Data professionals hired for entry level jobs.

• Surprisingly, among individual contributors at levels 1 and 2, non-U.S. citizens are paid

higher salaries than U.S. citizens.

• Firms on the West Coast pay the highest salaries to individual contributors, while firms in

the Northeast pay the highest salaries to managers.

• Firms in the consulting industry pay high salaries to both individual contributors and

managers, while firms in the tech/telecom industry also pay high salaries to individualcontributors. Healthcare and pharmaceutical companies are also among those paying the

highest salaries to Big Data professionals.

• Salaries of Big Data professionals also vary with gender, but not nearly as much as the

salaries of practitioners of other professions. Across job levels, women in Big Data never

earn less than 90% of their male counterparts.


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Compensation by Job Level

Figure 10 shows the distribution of individual contributors and managers, overall median base

salary and the proportion eligible for a bonus. Figures 11 and 12 show median and mean base salary

of Big Data professionals by job level. For each job level, they also show the proportion eligible for

a bonus. For those who received a bonus, they show the median and mean values of the last bonus

received. Figures 13 and 14 show how much median base salary increases with level for individualcontributors and managers.

Not surprisingly, Big Data professionals who are managers make considerably more than those who

are individual contributors, and compensation also depends on job level.

• 58% of the professionals in the sample are individual contributors, and their median base

salary is $90,000. The median base salary of the 42% of the professionals who are

managers is $145,000.

• 66% of individual contributors are eligible for bonuses, and the median value of the last

bonus received is approximately $10,000. 83% of managers are eligible for bonuses, andthe median value of last bonus received is $29,250.

• For both individual contributors and managers, median base salary increases significantly

with level. In both cases, the median salary of professionals at level 3 is almost 80% higher

of those at level 1.

• For both individual contributors and managers, the proportion eligible for a bonus increases

in level, and the bonuses paid to those at level 3 are much greater than bonuses paid to

those at levels 1 or 2.

Managers

42%Individual

Contributors

58%

Median Base Salary

$145,000

Bonus Eligible83%

Median Base Salary

$90,000

Bonus Eligible66%

Figure 10. Distribution of Individual Contributors & Management


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Individual

Contributor

Job Level

Base SalaryBonus

Eligible

Actual Bonus

N 25% Median Mean 75% Median Mean

Level 1 386 $60,000 $65,000 $69,313 $80,000 54.9% $6,300 $7,783

Level 2 537 $70,500 $85,000 $84,908 $95,000 69.3% $8,840 $10,393Level 3 715 $95,000 $115,000 $117,647 $135,000 70.2% $15,425 $23,079

Manager

Job Level

Base Salary

Bonus

Eligible

Actual Bonus

N 25% Median Mean 75% Median Mean

Level 1 440 $104,000 $120,000 $119,466 $135,000 80.5% $18,000 $21,088

Level 2 592 $135,000 $151,500 $156,573 $175,000 83.8% $32,000 $38,012

Level 3 173 $190,000 $215,000 $230,318 $250,000 94.2% $62,750 $83,913

Figure 11. Compensation of Individual Contributors by Job Level

Figure 14. Median and Mean Base Salaries of

Managers by Job Level

$50,000

$70,000

$90,000

$110,000

$130,000

$150,000

$170,000

$190,000

$210,000

$230,000

$250,000

Level 1 Level 2 Level 3

Figure 13. Median and Mean Base Salaries of

Individual Contributors by Job Level

$50,000

$70,000

$90,000

$110,000

$130,000

$150,000

$170,000

$190,000

$210,000

$230,000

$250,000


MeanMedian

Figure 12. Compensation of Managers by Job Level


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Compensation by Education

Figures 15 through 18 show the distribution of the base salaries of Big Data professionals by

education, controlling for job level.

Among individual contributors of all job levels, base salary varies significantly with

education. An individual contributor with a Ph.D. is typically paid at least $15,000 more thanoe ith ol a Bahelo’s degee ad at least $, oe tha o e ith a Maste’s

degree.

Among managers at job level 1, those with a Ph.D. also make significantly more than those

ith a Bahelo’s degee ad soehat oe tha those ith a Maste’s degee.

A Ph.D. o Maste’s degee does ot appea to ig a highe sala aog oe seio

managers, perhaps because good performance in their jobs depends at least as much on

management skills as on technical skills.


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Note: Individuals with no degrees were excluded because of the small sample size.

$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

$100,000

$110,000

$120,000

$130,000


Bachelor's Master's PhD, ABD PhD

Job Level Education Base SalaryN 25% Median Mean 75%

Individual

Contributor,

Level 1

Bachelor's 48 $53,500 $59,500 $59,565 $65,000

Master's 255 $60,000 $65,000 $68,401 $75,000

PhD, ABD 2 - - - -PhD 46 $70,000 $81,000 $81,359 $90,000

Individual

Contributor,

Level 2

Bachelor's 70 $70,000 $76,000 $80,260 $93,000

Master's 340 $70,000 $82,000 $82,945 $93,000

PhD, ABD 10 $65,000 $84,500 $84,850 $100,000

PhD 78 $85,000 $95,000 $97,631 $110,000

Individual

Contributor,

Level 3

Bachelor's 93 $86,000 $108,000 $112,097 $130,000

Master's 426 $90,000 $110,000 $114,763 $130,000

PhD, ABD 17 $110,000 $130,000 $128,941 $141,000

PhD 120 $105,000 $122,950 $126,799 $140,000

Figure 15. Base Salary of Individual Contributors by Job Level and Education

Figure 16. Median Base Salary of Individual Contributors by Job Level and Education


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Note: Individuals with no degrees were excluded because of the small sample size.

$90,000

$110,000

$130,000

$150,000

$170,000

$190,000

$210,000

$230,000

$250,000


Bachelor's Master's PhD, ABD PhD

Job Level Education Base SalaryN 25% Median Mean 75%

Manager,

Level 1

Bachelor's 48 $87,500 $105,000 $108,635 $125,000

Master's 275 $105,000 $120,000 $119,463 $135,000

PhD, ABD 9 $120,000 $135,000 $135,444 $141,000PhD 72 $112,000 $125,000 $127,211 $142,500

Manager,

Level 2

Bachelor's 62 $140,000 $160,000 $159,065 $175,000

Master's 322 $130,000 $150,000 $153,350 $172,000

PhD, ABD 12 $145,500 $165,000 $166,250 $188,000

PhD 137 $145,000 $160,000 $163,515 $180,000

Manager,

Level 3

Bachelor's 18 $200,000 $238,000 $268,667 $275,000

Master's 87 $190,000 $210,000 $229,893 $250,000

PhD, ABD 5 $210,000 $220,000 $221,800 $224,000

PhD 46 $190,000 $215,000 $224,761 $240,000

Figure 17. Base Salary of Managers by Job Level and Education

Figure 18. Median Base Salary of Managers by Job Level and Education


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Special Report:

Compensation for Entry Level Jobs by Education

In a separate analysis, Burtch Works analyzed compensation data for 93 Big Data professionals who

recently completed school and are in their first job earning their starting salary. Not surprisingly,

these et leel salaies deped o hat degee as eaed.

• The mean entry level salary of the entire sample is $63,000.

The mean et leel sala of the suset ho hae just opleted a Bahelo’s degee is

$52,000.

The mean et leel sala of those ho hae opleted a Maste’s degee is $,.

The mean entry level salary of professionals who have earned a Ph.D. is a much greater

$73,000.

61% of all Big Data professionals in their first jobs are eligible for a bonus.

Only 17% of Big Data professionals in their first jobs receive a sign-on bonus. For those who

did, the average bonus is $5,000.

Entry level data scientists were excluded from this sample.

Figure 19. Mean Entry Level Salary by Education

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

Bachelor's Master's PhD

Figure 20. Bonuses for Entry Level Jobs

No

39%

Yes

61%

Bonus Eligible

No

83%

Yes

17%

Sign-On Bonus

Bonus Percentage:

3% to 20%

Average Sign-On Bonus:

$5,000


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Compensation by Residency Status

Figures 21 and 22 shows how the median base salaries of Big Data professionals who are not U.S.

citizens vary from the salaries of those who are, controlling for job level.

Unexpectedly, individual contributors at job levels 1 and 2 who are not U.S. citizens have higher

salaries than those who are. There are several possible explanations for this.

• Non-U.S. citizens perform well in school because they would not be at schools in the U.S.

unless they were among the best and the brightest of the youths in their home countries.

Moreover, once here, they focus almost solely on the studies that brought them to the

United States.

• Once they have completed their studies, non-U.S. citizens conduct more thorough job

searches, because they require a job with a company that will sponsor their application for

an H-1B visa and support them as they seek permanent residency.

•

Non-U.S. citizens are more willing to work anywhere in the U.S., which affords them a largerchoice of jobs.

Among more senior managers, salaries of non-U.S. citizens are more similar to those of U.S. citizens.

Among the most senior individual contributors, salaries of non-U.S. citizens are considerably less.

The explanations include:

• By the time individuals born abroad become senior Big Data professionals, they have also

become U.S. citizens. Consequently, the salary data for senior Big Data professionals who

are U.S. citizens includes salaries for many individuals who were once non-U.S. citizens.

•

If a Big Data professional is at senior job level but has not yet obtained U.S. citizenship, it isoften a sign that he has made strategic errors in the advancement of his career, and his

salary might reflect this.


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Job LevelResidency

Status N

Median

Base Salary

Difference from

Citizen Base Salary

Manager,Level 1

Citizen 250 $120,000 0%

Perm Res 90 $122,500 +2%

H-1B 58 $110,000 -8%

F-1/OPT 2 - -

Other 7 $85,000 -29%

Manager,

Level 2

Citizen 397 $154,000 0%

Perm Res 118 $150,000 -3%

H-1B 19 $165,000 +7%

F-1/OPT 1 - -

Other 3 - -

Manager,

Level 3

Citizen 135 $215,000 0%

Perm Res 22 $222,500 +3%

H-1B 1 - -

Job LevelResidency

Status N

Median

Base Salary

Difference from

Citizen Base Salary

Individual

Contributor,

Level 1

Citizen 151 $62,000 0%

Perm Res 33 $71,200 +15%

H-1B 142 $70,000 +13%

F-1/OPT 24 $65,000 +5%

Other 3 - -

Individual

Contributor,

Level 2

Citizen 206 $81,500 0%

Perm Res 124 $87,250 +7%

H-1B 159 $82,500 +1%

F-1/OPT 2 - -

Other 10 $80,000 -2%

Individual

Contributor,

Level 3

Citizen 473 $115,000 0%

Perm Res 144 $110,050 -4%

H-1B 33 $103,000 -10%

F-1/OPT 2 - -

Other 8 $96,000 -17%

Figure 21. Median Base Salary of Individual Contributors by Job Level and

Residency Status

Figure 22. Median Base Salary of Managers by Job Level and Residency Status


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Compensation by Region

Figures 23 through 26 show the distributions of the base salaries of Big Data professionals by

region, controlling for job level.

Regardless of job level, individual contributors employed by firms on the West Coast are

paid the highest salaries. Among those at job level 1, the difference is $15,000. Thedifference declines at more senior job levels.

On the other hand, managers are paid the highest salaries by firms in the Northeast.

The regional differences in salaries are not as great as the regional differences in many costs

of living, such as housing and taxes.


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$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

$100,000

$110,000

$120,000

$130,000


West Coast Mountain Midwest Southeast Northeast

Job Level RegionBase Salary

N 25% Median Mean 75%

IndividualContributor,

Level 1

Northeast 118 $60,000 $65,000 $69,235 $78,000

Southeast 45 $60,000 $65,000 $67,753 $70,000

Midwest 128 $55,000 $65,000 $65,196 $75,000

Mountain 20 $57,500 $65,500 $69,393 $79,000

West Coast 38 $63,000 $80,000 $79,225 $90,000

Individual

Contributor,

Level 2

Northeast 147 $74,000 $86,000 $87,697 $100,000

Southeast 58 $70,000 $78,000 $78,966 $86,000

Midwest 182 $70,000 $85,000 $82,543 $92,000

Mountain 32 $70,500 $83,500 $84,516 $96,000

West Coast 79 $72,000 $90,000 $90,690 $105,000


Level 3

Northeast 204 $100,000 $120,000 $122,352 $135,000

Southeast 81 $90,000 $110,000 $113,049 $130,000Midwest 217 $88,000 $105,000 $110,084 $126,000

Mountain 53 $90,000 $110,000 $113,232 $133,000

West Coast 100 $102,500 $120,000 $126,795 $140,000

Figure 23. Distribution of Base Salaries of Individual Contributors by Job Level and Region

Figure 24. Median Base Salary of Individual Contributors by Job Level and Region


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$50,000

$70,000

$90,000

$110,000

$130,000

$150,000

$170,000

$190,000

$210,000

$230,000

$250,000


West Coast Mountain Midwest Southeast Northeast

Job Level RegionBase Salary

N 25% Median Mean 75%

Manager,Level 1

Northeast 122 $110,000 $130,000 $126,763 $140,000

Southeast 45 $95,000 $115,000 $119,178 $135,000

Midwest 151 $100,000 $117,000 $116,957 $135,000

Mountain 33 $105,000 $115,000 $111,833 $125,000

West Coast 50 $100,000 $115,500 $118,140 $133,000

Manager,

Level 2

Northeast 184 $145,000 $160,000 $165,687 $185,000

Southeast 67 $121,000 $145,000 $143,725 $165,000

Midwest 169 $134,000 $150,000 $151,790 $169,000

Mountain 41 $130,000 $148,000 $147,549 $165,000

West Coast 70 $140,000 $154,000 $163,100 $185,000

Manager,

Level 3

Northeast 63 $203,000 $230,000 $242,254 $265,000

Southeast 16 $192,500 $222,500 $219,063 $247,500

Midwest 46 $189,000 $206,000 $220,146 $241,000

Mountain 5 $210,000 $220,000 $341,000 $250,000

West Coast 28 $185,500 $200,000 $222,000 $228,000

Figure 25. Distribution of Base Salaries of Managers by Job Level and Region

Figure 26. Median Base Salary of Managers by Job Level and Region


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Compensation by Industry

Figures 27 through 30 show distributions of base salaries of Big Data professionals by industry,

controlling for job level

Firms in the tech/telecom industry pay individual contributors high salaries, particularly the

most junior individual contributors. This is partly because so many of these firms are locatedon the West Coast, where the competition for young talent is particularly fierce.

Consulting firms pay high salaries to both individual contributors and managers. This is to

attract and retain professionals to jobs that can require long work days and frequent travel.

Healthcare and pharmaceutical companies are also among those paying the highest base

salaries to Big Data professionals. This too is at least partly because such a large proportion

of these firms are located in the Northeast and on the West Coast, where the cost of living is

high.


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Job Level Industry Base SalaryN 25% Median Mean 75%


Level 1

Advertising/Mktg Services 81 $56,000 $62,000 $63,702 $68,000

Consulting 20 $64,000 $70,000 $75,170 $87,500

CPG 2 - - - -

Financial Services 97 $60,000 $70,000 $72,781 $82,500Healthcare/Pharma 7 $60,000 $67,500 $69,071 $80,000

Outsourcing 6 $60,000 $66,500 $65,833 $72,000

Retail 20 $56,500 $65,000 $65,400 $75,000

Tech/Telecom 12 $74,000 $91,000 $91,125 $105,000

Other 30 $55,000 $61,433 $65,807 $75,000

Individual

Contributor,Level 2


Consulting 30 $85,000 $95,000 $103,600 $120,000

CPG 1 - - - -

Financial Services 150 $76,000 $85,000 $86,149 $96,000

Healthcare/Pharma 10 $80,000 $93,000 $92,550 $105,000Outsourcing 14 $70,000 $79,000 $79,429 $89,500

Retail 27 $62,500 $76,000 $76,852 $85,000

Tech/Telecom 23 $85,000 $90,000 $93,500 $100,000

Other 36 $75,000 $86,250 $85,528 $95,000

Individual

Contributor,

Level 3


Consulting 40 $120,000 $130,000 $136,313 $154,000

CPG 12 $105,000 $116,500 $120,625 $134,750


Healthcare/Pharma 30 $97,000 $113,000 $119,600 $135,000

Outsourcing 4 - - - -Retail 33 $90,000 $100,000 $104,842 $115,000

Tech/Telecom 43 $99,000 $125,000 $123,209 $140,000

Other 43 $82,000 $105,000 $102,826 $120,000

Figure 27. Distribution of Base Salaries of Individual Contributors by Job Level and Industry


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$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

$100,000

$110,000

$120,000

$130,000


Advertising/Marketing Svcs. Consulting Consumer Packaged Goods

Financials Svcs. Healthcare/Pharma Outsourcing

Retail Tech/Telecom Other

Figure 28. Median Base Salary of Individual Contributors by Job Level and Industry


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Job Level Industry Base SalaryN 25% Median Mean 75%

Manager,

Level 1


Consulting 27 $115,000 $130,000 $129,330 $150,000

CPG 6 $120,000 $127,500 $125,667 $134,000

Financial Services 122 $105,000 $120,000 $121,804 $135,000Healthcare/Pharma 16 $118,000 $135,000 $133,040 $144,500

Outsourcing 5 $85,000 $96,000 $101,900 $100,000

Retail 26 $105,000 $111,000 $115,519 $130,000

Tech/Telecom 22 $115,000 $122,500 $123,477 $130,000

Other 28 $96,500 $116,500 $115,732 $128,000

Manager,

Level 2


Consulting 35 $150,000 $175,000 $168,957 $190,000

CPG 20 $147,500 $161,250 $166,837 $177,000


Healthcare/Pharma 25 $140,000 $155,000 $154,340 $165,000Outsourcing 6 $135,000 $150,000 $150,833 $170,000

Retail 40 $130,000 $151,000 $154,450 $173,500

Tech/Telecom 24 $137,000 $150,000 $162,333 $195,000

Other 34 $139,000 $149,500 $152,971 $170,000

Manager,

Level 3


Consulting 12 $215,000 $247,500 $289,750 $298,500

CPG 5 $220,000 $225,000 $233,000 $260,000


Healthcare/Pharma 14 $195,000 $200,000 $215,000 $250,000

Outsourcing 2 - - - -Retail 9 $180,000 $190,000 $204,222 $237,000

Tech/Telecom 7 $186,000 $195,000 $204,714 $210,000

Other 7 $125,000 $195,000 $177,857 $220,000

Figure 29. Distribution of Base Salaries of Managers by Job Level and Industry


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$90,000

$110,000

$130,000

$150,000

$170,000

$190,000

$210,000

$230,000

$250,000


Advertising/Marketing Svcs. Consulting Consumer Packaged Goods

Financials Svcs. Healthcare/Pharma Outsourcing

Retail Tech/Telecom Other

Figure 30. Median Base Salary of Managers by Job Level and Industry


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Compensation by Gender

The Burtch Works Study has shown that base salaries of Big Data professionals vary with job level,

education, residency status, region and industry. The salaries of Big Data professionals also vary

with gender, but not nearly as much as the salaries of practitioners of other professions.

Across the entire U.S. labor market, the average compensation of a woman is 77% of the averagecompensation of a man. However, among Big Data professionals at the same job level, the ratio of

the median salary of women to the median salary of men is no smaller than 90%. For the more

junior job levels, at which most Big Data professionals are employed, the ratio is never less than

94%.

Figure 31. Median Base Salary by Job Level and Gender

$60,000

$80,000

$100,000

$120,000

$140,000

$160,000

$180,000

$200,000

$220,000

IC, Level 1 IC, Level 2 IC, Level 3 MG, Level 1 MG, Level 2 MG, Level 3

Men Women

98%

94%

91%

96%

97%

90%


38/47


Section 5

SPECIAL REPORT: SALARY INCREASES OF

BIG DATA PROFESSIONALS

WHO CHANGE JOBS


39/47


40/47


Base Salary Change by Job Title

Figure 33 shows the average increase in base salary by new title of the Big Data professionals who

changed jobs.

• Salary increases were far larger for professionals taking senior jobs. The average increase

for a professional taking a job as a Vice President was almost $25,000, about twice theincrease of a professional taking a job as a Manager.

• However, percentage salary increases were larger for professionals moving to junior jobs

than for those moving to senior jobs. The average percentage increase for a professional

taking a job with an Analyst title was 14.1%, while the average percentage increase for a

professional taking a Vice President job was 12.6%.

Figure 33. Average Salary Increase by New Job Title

$0

$5,000

$10,000

$15,000

$20,000

$25,000


41/47


Base Salary Change by Education

Figure 34 shows the average increase in base salary by education for the Big Data professionals who

changed jobs.

• Salary increases were larger for a professional changing jobs if they had an advanced

degree. The average increase for professionals with a Ph.D. was over $18,000, while it wasappoiatel $, fo those ith a Bahelo’s degee.

• Percentage salary increases were also larger for professionals with a Ph.D. The average

increase for a professional with a Ph.D. changing jobs was 16%, while it was 14% for those

ith a Bahelo’s degee.

Figure 34. Average Percentage Salary Increase by

$0

$5,000

$10,000

$15,000

$20,000

$25,000

Bachelor's Master's PhD


42/47


Section 6

WHERE DO WE GO FROM HERE?

Recruiting & Retaining Big Data Professionals


43/47


Recruiting & Retaining Big Data Professionals

Since the Great Recession began, most professions have experienced weak demand for their

practitioners. The Big Data profession has been an exception. Now, as economic growth in the

U.S. accelerates, it will become even more difficult to hire and retain Big Data professionals. What

advice does Burtch Works have?

• Firms must increase pay for Big Data professionals. Salary bands for Big Data professionals

have not changed much in the past several years. Firms will need to shift these bands to

successfully retain Big Data professionals. As the Burtch Works Study has shown, these

professionals currently realize large increases in compensation when they change jobs.

• Firms must be willing to sponsor applications for visas or transfers of visas of Big Data

professionals who are foreign nationals.

• To be more effective, online sourcing of candidates must be more targeted. Corporate

sourcing specialists are intensively using LinkedIn to identify candidates for Big Data jobs at

their firms. However, because they then contact so many prospects, Big Data professionalshae egu to oplai of euite fatigue ad often decline to discuss job opportunities

when contacted.

• Those hiring Big Data professionals must prioritize the skills and experience required,

because it will become increasingly difficult to attract individuals with all of the desired

qualifications.

• Firms should consider the alternative of training: equipping current staff with the

methodological and software skills needed to exploit Big Data.

And, of course, those seeking Big Data professionals should’t e elutat to contact Burtch Worksfor advice and support:

Burtch Works LLC

1560 Sherman Ave Suite 1005

Evanston, IL 60201

Call: 847-440-8555

Email: [email protected]

mailto:[email protected]:[email protected]:[email protected]


44/47


Section 7

APPENDIX


45/47


Glossary of Terms

This section provides definitions of terms used in this report.

ABD (All-but-dissertation). ABD is a level of education. A person whose level of education level is ABD

has completed all coursework for a Ph.D. except for a dissertation.

Base Salary. A idiidual’s goss aual ages, eludig aiale o oe-time compensation such asrelocation assistance, sign-on bonuses, bonuses, and long-term incentive plan compensation.

Big Data Professionals. Individuals who can apply sophisticated quantitative skills to data describing

transactions, interactions, or other behaviors of people to derive insights and prescribe actions. They

ae distiguished fo the uats of the past the shee uatit of data o hih the opeate, a

abundance made possible by new opportunities for measuring behaviors and advances in technologies

for the storage and retrieval of data.

Bonus. Short-term variable compensation usually awarded annually, such as individual or company

performance-based bonuses. This does not include long-term incentive plan compensation or awards of

stock or stock options.

Data Scientist. A Big Data professional who has both the proficiency for data management required to

make Big Data accessible and also the analytical skills for deriving useful information from Big Data.

Entry-level job. A job available to individuals who have no prior work experience, but usually have just

earned an undergraduate or graduate degree.

F-1/OPT. A residency status that allows a foreign undergraduate or graduate student who has a non-

immigrant F-1 student visa to work in the U.S. without obtaining an H-1B visa. The student is required

to have either completed his degree or pursued it for at least nine months.

Geographic Region. One of five groups of states that together comprise the entire United States. These

five groups of states – Northeast, Southeast, Midwest, Mountain and West Coast – are shown in Figure 3

on page 10.

H-1B. A non-immigrant visa that allows a U.S. firm to temporarily employ a foreign worker in a specialty

occupation for a period of three years, which is extendable to six and beyond. If a foreign worker withan H-1B visa quits or loses his job with the sponsoring firm, the worker must either find a new employer

to sponsor an H-1B visa, be granted a new non-immigrant status, or leave the United States.

Individual Contributor. An employee who does not manage other employees. Individual contributors

among the Big Data professionals in the Burtch Works sample have all been assigned to one of three

levels:

Level 1: Responsible for learning the job; hands-on with analytics and modeling; 0- eas’

experience

Level 2: Hands-on with data, working with more advanced problems and models; may help train

Analysts; 4-8 years of experience

Level 3: Cosideed a aaltis “ujet Matte Epet; etos ad tais aalsts; + eas’experience

Industry. One of nine groups of firms employing most data professionals. These nine industries are

Advertising/Marketing Services, Consulting, Consumer Packaged Goods, Financial Services,

Healthcare/Pharmaceuticals, Outsourcing, Retail, Tech/Telecom and Other.

Advertising/Marketing Services: An industry consisting of firms that provide services to other

firms that include advertising, market research, media planning and buying, and marketing

analysis.


46/47


Consulting: Industry that includes both large copoatios ad sall outiue fis that

provide professional advice to the managers of other firms.

Consumer Packaged Goods: Companies whose products are sold quickly and at relatively low

cost, including non-durable goods (e.g. groceries, toiletries) and lower-quality consumer

electronics.

Financial Services: Firms that provide services related to the finance industry, which

encompasses a broad range of organizations that manage money including banks, insurance

companies, and credit card organizations.

Healthcare/Pharmaceuticals: Sector that includes companies that provide patients with

healthcare services, and firms that manufacture medicinal drugs.

Outsourcing: Companies whose primary workforce is contracted by their clients, in order to

move labor out of the internal business process to a third party organization. Many outsourcing

companies utilize off-shore resources to complete work for clients.

Retail: Organizations that purchase goods from a manufacturer to be sold for profit to the end-

consumer.

Tech/Telecom: Industry that includes companies that provide telecommunications services in

addition to organizations that focus on creating or distributing technology products or services.

Other: Companies whose industry falls outside of the eight categories delineated above, such as

airline companies, distribution firms, media, and entertainment.

Manager. An employee who manages the work of other employees. Managers among the Big Data

professionals in the Burtch Works sample have all been assigned to one of three levels:

Level 1: Tactical manager who leads a small group within a function, responsible for executing

limited-scale projects or tasks within a project; typically responsible for 1-3 direct reports or

matrix individuals.

Level 2: Manager who leads a function and manages a moderately sized team; responsible for

executing strategy; typically responsible for 4-9 direct reports or matrix individuals.

Level 3: Member of senior management who determines strategy and leads large teams;

manages at the executive level; typically responsible for 10+ direct reports or matrix individuals.

Mean. Also known as the average, it is the sum of a set of values divided by the number of values. For

example, the mean of N salaries is the sum of the salaries divided by N.

Median. The value obtained by ordering a set of numbers from smallest to largest and then taking the

value in middle, or, if there are an even number of values, by taking the mean of the two values in the

middle. For example, the median of N salaries is the salary for which there are as many salaries that are

smaller as there are salaries that are larger.

N. The number of observations in a sample, sub-sample or table cell.

OPT. See F-1/OPT.

Permanent Resident. A residency status that allows a foreign national to permanently live and work in

the United States. Those with this status have a United States Permanent Residence Card, which is

known informally as a green card.

Salary Study. A study conducted to measure the distributions by salary of those in specific occupations.

Traditionally, these studies have been executed by obtaining salary data from the human resources

departments of firms employing professionals in those occupations rather than by interviewing those

employees themselves.

STEM. Acronym for the fields of Science, Technology, Engineering and Mathematics.


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ABOUT BURTCH WORKS

Burtch Works is a specialized executive recruiting firm dedicated to placing highly qualified quantitative

professionals in analytics roles nationwide. By maintaining constant contact with hundreds of staffers,

hiring managers and human resources professionals every month, we are able to follow developing

trends in the high growth field of marketing analytics. In addition, we are continuously tracking talent

movement and industry changes that are creating new jobs every day. Leveraging our massive and

unique network of quantitative professionals, we can ensure that we find the best possible fit for both

our candidates and our clients.

We pride ourselves on our reputation as the premier source of the best jobs in the quantitativemarketing field, and we welcome complete and thorough feedback on our work as we go through the

recruiting process. If you are looking to build a first class analytics staff or if you are considering a job

change yourself, we encourage you to contact us.

CONTACT US

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