The. Burtch. Works. Study. Salaries for Big Data Professionals July Burtch Works Executive Recruiting Linda Burtch, Managing Director

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The

Study

Salaries for Big Data Professionals

July 2013

Burtch Works Executive Recruiting

Linda Burtch, Managing Director

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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 ... 15

Education 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

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Section 1

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Study Objective

The purpose of this report is to provide up-to-date information on the compensation of “Big Data professionals.” Big Data professionals are individuals who can apply sophisticated quantitative skills to data describing transactions, interactions or other behaviors of people to derive insights and prescribe actions. They are distinguished from the “quants” of the past by the sheer quantity 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 in analytics 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 currently serving as the Board’s President.

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 starting with the completion of their Master’s and Ph.D. programs. As these individuals progress in

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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 with deep 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 because a firm’s Big Data professionals are typically not in a department that is only for such 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 the professionals 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 typically done 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

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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 an interview 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 – usually an advanced one, such as a Master’s degree 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 Data professionals 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 as customer 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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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 also knowledge 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 of management responsibility, and if not, the depth of expertise:

Individual Contributors

Level Responsibility Typical 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 Responsibility Typical Number

of Reports

Level 1 Tactical manager who leads a small group 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

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 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

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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

 Bachelor’s degree

 Master’s degree

 Ph.D. all-but-dissertation (ABD)

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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 professionals are highly educated. 86% have at least a Master’s degree.

• 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+ Numbe r o f Pro fess io na ls 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: “3 men to every 1 woman” in the field1

Computer Science: “women comprise 27-29% of the computing workforce”2

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+ Year s' E xp e ri e n ce Male Female

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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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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% IC, Level 1 IC, Level 2 IC, Level 3 MG, Level 1 MG, Level 2 MG, Level 3

Citizen Perm. Resident H-1B F-1/OPT Other

Residency Status of Big Data Professionals

A large proportion of the Big Data professionals, 39%, are not U.S. citizens:

Fewer than half of individual contributors at levels 1 and 2 are U.S. citizens, while majorities of individual contributors at level 3 and managers at all levels are U.S. citizens:

Citizen 61% Perm. Resident 20% H-1B 17% F-1/OPT 1% Other 1%

Figure 7. Big Data Professionals by Residency Status

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Will not transfer 27% Will transfer 67% Will transfer exceptional talent 6% All Industries 22% 70% 8% Consulting/Advertising 42% 50% 8% Retail 23% 77% Corporate (non-retail)

professionals are from abroad, most companies employing these professionals are willing to sponsor applications to obtain or transfer visas:

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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 individual contributors. 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 individual contributors 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, and the 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 Eligible 83%

Median Base Salary $90,000

Bonus Eligible 66%

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Individual Contributor Job Level Base Salary Bonus 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 $10,393 Level 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

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 Mean Median

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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 than one with only a Bachelor’s degree and at least $13,000 more than one with a Master’s degree.

 Among managers at job level 1, those with a Ph.D. also make significantly more than those with a Bachelor’s degree and somewhat more than those with a Master’s degree.

 A Ph.D. or Master’s degree does not appear to bring a higher salary among more senior 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

Level 1 Level 2 Level 3

Bachelor's Master's PhD, ABD PhD

Job Level Education Base Salary

N 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

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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

Level 1 Level 2 Level 3

Bachelor's Master's PhD, ABD PhD

Job Level Education Base Salary

N 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 $141,000 PhD 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

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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 “entry level salaries” depend on what degree was earned.

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

 The mean entry level salary of the subset who have just completed a Bachelor’s degree is $52,000.

 The mean entry level salary of those who have completed a Master’s degree is $63,000.

 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

$30,000 $40,000 $50,000 $60,000 $70,000

Figure 20. Bonuses for Entry Level Jobs

No 39% Yes 61% Bonus Eligible Sign-On Bonus Bonus Percentage: 3% to 20%

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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 larger choice 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 is

often 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 Level Residency

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%

Job Level Residency

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

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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. The difference 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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$50,000 $60,000 $70,000 $80,000 $90,000 $100,000 $110,000 $120,000 $130,000

Job Level Region Base Salary

N 25% Median Mean 75% Individual Contributor, 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 Individual Contributor, Level 3 Northeast 204 $100,000 $120,000 $122,352 $135,000 Southeast 81 $90,000 $110,000 $113,049 $130,000 Midwest 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

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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

Level 1 Level 2 Level 3

West Coast Mountain Midwest Southeast Northeast

Job Level Region Base 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

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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 located on 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 Salary N 25% Median Mean 75% Individual Contributor, 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 $82,500 Healthcare/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 Advertising/Mktg Services 107 $70,000 $80,000 $82,918 $95,000 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 $105,000 Outsourcing 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 Advertising/Mktg Services 98 $92,000 $107,500 $111,983 $133,000 Consulting 40 $120,000 $130,000 $136,313 $154,000 CPG 12 $105,000 $116,500 $120,625 $134,750 Financial Services 198 $95,000 $110,000 $121,018 $135,000 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

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$40,000 $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 $110,000 $120,000 $130,000

Level 1 Level 2 Level 3

Advertising/Marketing Svcs. Consulting Consumer Packaged Goods Financials Svcs. Healthcare/Pharma Outsourcing

Retail Tech/Telecom Other

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Job Level Industry Base Salary N 25% Median Mean 75% Manager, Level 1 Advertising/Mktg Services 96 $106,500 $120,000 $120,254 $135,000 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 $135,000 Healthcare/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 Advertising/Mktg Services 137 $140,000 $153,000 $158,779 $178,000 Consulting 35 $150,000 $175,000 $168,957 $190,000 CPG 20 $147,500 $161,250 $166,837 $177,000 Financial Services 129 $126,000 $147,000 $150,881 $165,000 Healthcare/Pharma 25 $140,000 $155,000 $154,340 $165,000 Outsourcing 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 Advertising/Mktg Services 54 $199,000 $225,000 $227,504 $250,000 Consulting 12 $215,000 $247,500 $289,750 $298,500 CPG 5 $220,000 $225,000 $233,000 $260,000 Financial Services 15 $201,000 $225,000 $278,400 $250,000 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

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$90,000 $110,000 $130,000 $150,000 $170,000 $190,000 $210,000 $230,000 $250,000

Level 1 Level 2 Level 3

Advertising/Marketing Svcs. Consulting Consumer Packaged Goods Financials Svcs. Healthcare/Pharma Outsourcing

Retail Tech/Telecom Other

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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 average compensation 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%

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Section 5

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Overview

In a separate analysis, Burtch Works was able to assess salary change data for 172 Big Data professionals who changed jobs over the past 18 months, ending with February, 2013. Burtch Works recorded the salaries earned by these professionals both before and after the job change, so it could measure how much the salary of a Big Data professional typically changes when he changes jobs. Figure 32 shows the distribution of salary changes.

• The average salary increase was 14%.

• Salary increases varied from 0% to 50%, but almost two-thirds (65%) were between 6% and 15%.

Figure 32. Number of Big Data Job Changes by Percentage Change in Base Salary

0 5 10 15 20 25 30 35 40 0% 1-5% 6-10% 11-15% 16-20% 21-25% 26-30% 31-35% 36-40% 41-45% 46-50% Numbe r o f C and ida te s

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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 the increase 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

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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 was approximately $12,000 for those with a Bachelor’s degree.

• 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 with a Bachelor’s degree.

Figure 34. Average Percentage Salary Increase by Education $0 $5,000 $10,000 $15,000 $20,000 $25,000 Bachelor's Master's PhD

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Section 6

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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 professionals have begun to complain of “recruiter fatigue” and 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 shouldn’t be reluctant to contact Burtch Works for advice and support:

Burtch Works LLC

1560 Sherman Ave Suite 1005 Evanston, IL 60201

Call: 847-440-8555

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Section 7

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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. An individual’s gross annual wages, excluding variable or one-time compensation such as

relocation 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 are distinguished from the “quants” of the past by the sheer quantity of data on which they operate, an 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 with an 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; 0-3 years’

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: Considered an analytics Subject Matter Expert; mentors and trains analysts; 9+ years’

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.

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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.

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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 quantitative marketing 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

If your organization needs assistance in quantitative or market research staffing, please email

clients@burtchworks.com. If you are a job seeker, please email candidates@burtchworks.com. For

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