Letter of Notification for a Master of Science in Data Science

Table of Contents ACADEMIC PROGRAM NAME ...... 3

DEGREE DESIGNATION ...... 3

PROPOSED CIP CODES ...... 3

PROPOSED CIP CODES TITLE ...... 3

PROPOSED IMPLEMENTATION DATE ...... 3

ACADEMIC PROGRAM LIAISON (APL) NAME AND CONTACT INFORMATION ...... 3

BACKGROUND CONCERNING ACADEMIC PROGRAM DEVELOPMENT ...... 3

PURPOSE AND NATURE OF ACADEMIC PROGRAM ...... 4

ALIGNMENT WITH STATE MASTER PLAN AND INSTITUTIONAL MISSION ...... 5

INSTITUTIONAL CAPACITY TO DELIVER THE PROPOSED ACADEMIC PROGRAM ...... 8

EXISTING PROGRAMS OFFERED AT PUBLIC AND PRIVATE TENNESSEE INSTITUTIONS ...... 8

FEASIBILITY STUDY ...... 9

PROGRAM COSTS/REVENUES ...... 19

THEC FINANCIAL PROJECTION FORM ...... 20

REFERENCES ...... 21

APPENDIX A: THEC Financial Projections Form ...... 22

APPENDIX B: Letters of Support ...... 28

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ACADEMIC PROGRAM NAME Data Science

DEGREE DESIGNATION Master of Science (MS)

PROPOSED CIP CODES 11.0701 (Computer Science)

PROPOSED CIP CODES TITLE Computer Science (11.0701)

PROPOSED IMPLEMENTATION DATE Fall 2020

ACADEMIC PROGRAM LIAISON (APL) NAME AND CONTACT INFORMATION Dr. Robin Poston, [email protected], 901.678.5739

BACKGROUND CONCERNING ACADEMIC PROGRAM DEVELOPMENT “The coming century is surely the century of data” (Donoho, 2000). Data Science is emerging as a new, transformative paradigm in science and technology. With large volumes of data being generated every day from multiple sources (including business data, biomedical data, educational data, science data, engineering data, and personal data), the importance of systematic and rigorous approaches to understanding and putting these large volumes of data to good use is now well recognized. With this explosion of data, there is a significant demand for experts in industry, government, education, healthcare, etc., that have requisite skills to collect, process, and analyze data. Indeed, demand for Data Science master’s degrees has exploded in the last couple of years as indicated by the fact that the number of master’s degrees awarded in this area has quadrupled from around 5,000 to around 20,000 between 2016 and 2018 (see Figure 5). Our feasibility study, presented later, provides ample evidence on student interest and labor market needs in this area of Data Science including local and regional need, nationwide employer need, and future sustainable need and demand.

Human expertise bottleneck. As noted, data is being generated at an unprecedented rate from varied sources such as social media, sensors, vehicles, smartphones, etc. We can collect a variety of data at high velocity and in large volumes using various data collection devices (sensors). For instance, we can deploy billions of sensors in cellphones and cars and have the information they collect sent to a digital storage server; similarly, millions of people observe and reported instantly traffic information using their cellphones – this information is then shared with all other drivers improving the overall efficiency of the

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transportation system. Just to illustrate the volume of data being currently collected and available digitally, IBM estimates that 90 percent of the data in the world today has been created in the past two years.

Exploiting the large and diverse data (big data) offers tremendous opportunities to improve processing, products, and services (Berman et al., 2018) as big data is assumed to carry insights and knowledge which would otherwise be inaccessible (Cao, 2017). For instance, in healthcare, big data holds the promise of reducing costs and increasing the quality of services (Brennan & Bakken, 2015; Frakt & Pizer, 2016). In other areas such as social and behavioral sciences (Lazer et al., 2009), agriculture (Kirkpatrick, 2019), law & justice (Quemy, 2017; also see the Data Driven Justice Initiative at https://www.naco.org/resources/signature-projects/data-driven-justice and the Big Data Social Justice Initiative at http://www.bigdatasocialjustice.com/social-justice-initiatives), or government (www.data.gov), there are similar opportunities. To deliver on those promises, we need to solve, above all, the human expertise bottleneck challenge by increasing the number of students trained in and knowledgeable of Data Science.

Indeed, we can now scale data collection (by deploying at scale billions of data collection devices/sensors), storage (which is cheap and abundant), and processing (we can access millions of computers through cloud services). However, we cannot scale human expertise without a strategic, sustained, and concerted effort by all stakeholders. We face a human expertise bottleneck when it comes to big data.

To meet this demand, universities around the country and the world have designed and been offering degrees in Data Science (for instance, there are more than 500 programs listed on the www.datascience.community) or establish entire institutes (see University of Rochester’s Goergen Data Science Institute and many others), departments, or schools (see University of Virginia’s School of Data Science - https://news.virginia.edu/content/uva-plans-new-school-data-science-120-million-gift-largest- university-history). The State of Tennessee and in particular the West Tennessee region will greatly benefit from a master’s level program in Data Science as indicated later by our feasibility study. The proposed Master’s in Data Science will address this acute need for Data Scientists in West Tennessee and beyond.

PURPOSE AND NATURE OF ACADEMIC PROGRAM The purpose of the proposed Master of Science in Data Science (MS-DS) program is two-fold: 1) train students for positions in government and private agencies, industry, and research institutes, and 2) prepare students who plan to enter a doctoral program in Data Science and related fields. Among the outcomes of the MS-DS program we mention increase in State education attainment levels, meet the needs of economic, workforce, and research needs, and to increase degree production. The new MS-DS program will be hosted under the Dean of College of Arts and Sciences given its multi/inter disciplinary nature of its courses.

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The nature of the program includes core courses in theoretical foundations of Data Science, i.e., a set of Computer Science and Statistics courses, and elective courses in discipline-specific quantitative analysis methods. The elective courses are clustered in specific disciplines such as Economics or Biomedical. This model has been proposed based on a market analysis of top programs (Columbia University, University of Michigan, University of Rochester) as well as programs from peer universities (University of Texas at El Paso, Southern Methodist University) around the country. The model offers foundational training as well as discipline-specific training in Data Science thus enabling students to become Data Scientists in specific areas such as Biology, Economics, Public Health, Government Policy, Logistics and Transportation, Inventory Management, Information Technology, inter alia, and a variety of other data- driven fields.

This design should make the degree attractive to students who want to focus on Data Science methods in particular disciplines. It should be noted that one of the clusters is core Data Science which is meant to attract students who want to focus on core Data Science topics and possibly pursue a Ph.D. The target audience is college students who want to pursue Data Science careers with a focus on various disciplines ranging from political science to biology to public health to economics as well as professionals who want to acquire advanced Data Science skills in order to be able to advance their careers and competitiveness of their organizations by exploiting big data sets available nowadays with the goal of improving their organization’s processes, products, and services.

Specifically, the MS-DS degree requires completion of 33 semester credit hours as follows: 15 credits from a set of core courses, 15 credits from a list of electives (with the recommendation that 9 credits must be from a concentration area), and 3 credits as master’s project. A Master’s Thesis option (6 credits) is also available in which case only 12 credits are needed from the list of electives.

The delivery method will initially be on-ground and hybrid as only some of the courses are available both on-ground and online as of this writing. We anticipate having online courses available to offer a fully on-line degree in parallel to the on-the-ground degree 3 years from the start of the program.

ALIGNMENT WITH STATE MASTER PLAN AND INSTITUTIONAL MISSION The function of the State Master Plan includes holding accountable higher education programs for increasing the educational attainment levels of Tennesseans, being able to address the state’s economic development, workforce development, and research needs, and aiming to ensure increased degree production within the state’s capacity to support higher education. In addition, minimizing redundancy in degree offerings is another aspect of the State Master Plan. The proposed MS-DS program aligns with the State Master Plan noted above. The MS-DS program aims to increase State education attainment levels, meet the needs of economic, workforce, and research needs, and to increase degree production.

Based on a recent self-study conducted under the Data Science Initiative at The University of Memphis, we have identified a major need to offer a full graduate-level degree in Data Science. Indeed, the self-

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study revealed a number of gaps in our Data Science offerings at The University of Memphis. First, while we offer a number of graduate certificates in Data Science as a form of systematic graduate-level training in this area, there are no full-degrees offered. The table below lists these certificates. For instance, the School of Public Health offers a certificate in Health Analytics (established in 2016) which consists of 6 courses. Similarly, there is a Master’s in Bioinformatics and a certificate in Bioinformatics to fill the growing need for technical staff who can work with and analyze genomic data. These certificates do not offer the depth and breadth necessary for training Data Scientists due to their limitations in terms of the number of courses that could be included in such certificates.

Table 1. Graduate Certificates related to Data Science at The University of Memphis. Department Program Summary 2 required courses in core data Graduate Certificate in science and 2 electives that can Computer Science Data Science be chosen from a broad range of data science topics Graduate Certificate in 5 required courses School of Public Health Health Analytics predominantly in biostatistics 5 required courses distributed Graduate Certificate in Biology between computer science and Bioinformatics biostatistics Graduate Certificate in 4 courses with electives Business Information and Business Intelligence and distributed mainly between Technology Analytics computer science and MIS Graduate Certificate in 2 required courses and 3 Education Quantitative Studies in elective courses predominantly Educational Research in statistics

Second, while some programs, e.g., Psychology, at The University of Memphis do offer intensive training, over a number of courses, on certain aspects of data analysis (e.g. inferential statistics), they lack offerings in terms of basic programming and big data processing. A set of several courses introducing students to basic programming and computational data processing techniques, e.g., in the cloud, could be a solution.

Third, there is a lack of training in Machine Learning, an area of Computer Science that makes extensive use of data and which can offer domain experts a set of powerful tools that could be used to address key tasks in, say, biomedical sciences, e.g., predicting the right type of cancer based on gene expression level. Our proposed Master of Science degree will address these issues with training students at the necessary depth and breadth to become successful Data Scientists in a domain of their interest.

The proposed plan serves the institutional mission well. The University of Memphis is fully dedicated to preparing students with solid quantitative skills and competencies to apply to a wide variety of fields and prepare them for future endeavors in their career and subsequent studies. As seen in the objectives stated in the section of Purpose and Nature of the Program, the MS-DS program will bring a strong

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component of computational and statistical theory and in-depth innovative practical training opportunities, which will result in competitive graduate students who are more prepared for future career and research opportunities.

Furthermore, the proposed Master of Science program (in addition to the existing graduate certificates in Data Science) will have a strong potential to increase university enrollment overall, based on data from other universities. In addition, we expect the enrollment in related programs and courses outside the Data Science program will also increase due to the importance of data in all areas including socio- behavioral, engineering, humanities, and business and economics areas.

Enrollments in Data Science are growing fast as well. For instance, the Data Science program at The University of Berkeley “is the fastest-growing program in the history of Berkeley” according to a statement by University of Berkeley’s Provost Paul Alivisatos in front of the congressional subcommittee on research and technology in July 2017. At the University of Memphis, the Fundamentals of Data Science and Machine Learning courses are the largest graduate level courses, in terms of enrollment, in the department of Computer Science with more than 50 students enrolled on a regular basis and demand is growing. The graduate certification in Data Science is also the largest certificate in the department of Computer Science in terms or enrollment with 9 students being currently enrolled and many testimonials from our students during the so-called exit interview indicate the need for a full degree in Data Science.

Furthermore, in the Department of Biological Sciences, a department not typically known for an emphasis on Data Science, the recently developed graduate course Data Science for Biologists has received great interest and shown a consistent enrollment over the last two years of 12-13 students.

The fact that many students take Data Science related courses, or pursue Data Science related certificates as noted above, is yet another indication of the interest and importance of this field of study among our current students. Some of those students may want to pursue full degrees in Data Science, which is not currently possible at The University of Memphis. The only option they have is to pursue such a degree at another university, which would be a lost opportunity for The University of Memphis.

The main purpose of the proposed degree is to attract new students to The University of Memphis for careers in Tennessee. And, our main goal is to offer those who want to pursue a degree in Data Science the opportunity to do so here.. At the moment, because The University of Memphis does not offer the degree students do not have this option and it is a lost opportunity of The University of Memphis.

Existing certificates do not offer the depth and breadth necessary for training Data Scientists due to the limited number of courses included in such certificates. The new MS-DS program will offer a complete degree in Data Science which is high demand as recent growth of MS-DS degrees indicates (see Figure 5).

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The proposed degree is also based on market needs. Based on our research, demand for Data Scientists is growing fast. A recent study by Mckinsey states that "a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.)." Further, the report also states that there would be roughly four to five million jobs in the U.S. requiring data analysis skills by 2018. According to Glassdoor.com, “data scientist” was the number 1 job in America in 2016. In 2019, “data scientist” was found to be the most promising job (defined by high salary, high demand, continual growth, and potential for advancement) by LinkedIn.com. Local organizations such as St. Jude’s Research Hospital, AutoZone, and FedEx are investing heavily in data centers and are in much need for data scientists. Please see the letters of support in the Appendix B.

INSTITUTIONAL CAPACITY TO DELIVER THE PROPOSED ACADEMIC PROGRAM The University of Memphis has strong programs in core Data Science areas such as Computer Science and Statistics as well as discipline-specific data analysis expertise and course offerings (see the list of core courses and discipline-specific courses later). There is no need to develop new courses to have the program started. However, there is a need to provide an organizational structure and corresponding resources (e.g., Program Director, administrative assistant, etc. – see the Support Resources section) in order to run the program. The University of Memphis has the capacity and is committed to invest the necessary resources to have the proposed program started. We already offer a Data Science graduate certificate which will constitute the basis of the new MS-DS program. The departments of Computer Science and Mathematics have jointly developed this program proposal in close collaboration with other departments spanning different colleges including public health, biology, business and information technology, and economics. All these departments have agreed to collaborate in order to successfully implement the proposed program once approved. Given the fast growth in the area of Data Science we expect net gains in terms of enrollment. The goal is to offer potential students interested in pursuing a Data Science graduate degree the opportunity to do enroll at The University of Memphis as opposed to other institutions. Currently, The University of Memphis is missing on this great opportunity of attracting such students by not offering any Data Science degree despite extraordinary growth in this area (see the Feasibility Study section for details). For instance, the number of master’s degrees awarded in this area has quadrupled from around 5,000 to around 20,000 between 2016 and 2018 (see Figure 5).

EXISTING PROGRAMS OFFERED AT PUBLIC AND PRIVATE TENNESSEE INSTITUTIONS Lipscomb University in Nashville offers a MS in DS degree https://www.lipscomb.edu/academics/programs/data-science-graduate Vanderbilt University offers a 48-credit hour MS in DS program housed in the Data Science Institute https://www.vanderbilt.edu/datascience/academics/msprogram/admissions/).

There are a number of related programs. University of Tennessee at Chattanooga offers: (1) M.S. in Computer Science with Data Science Concentration and (2) M.S. in Data Analytics. Also, the University of Tennessee Knoxville offers a Ph.D. in Data Science and Engineering to which students who have completed a B.S. degree may be admitted.

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FEASIBILITY STUDY Our feasibility study focused on student interest and labor market evidence including local and regional need, nationwide employer need, and future sustainable need and demand. Feedback from our alumni and current students, as well as feedback from local and regional institutes and companies, are included in the study. In addition to these sources, we also provided data from different universities on enrollment in Master of Science in Data Science, as well as national data on the number of graduates from related programs (MS in Computer Science and MS in Statistics) and the need of Data Scientists in the job market. These are followed by data on future need and demand of Master level Data Scientists.

Student interest We investigated students’ interest from various perspectives. We surveyed current students and asked them about their interest in the MS-DS program. As an example, Lasang Tamang (his letter is attached), our graduate student, has expressed to our faculty members (Professor Vasile Rus) over a year ago about his interest in an MS in Data Science. He is eager to enhance his skills in computational and statistical methods to better prepare him for the projects he is working on. The MS in DS apparently is an excellent fit for local students like him. Steve Lee, who completed an MA in Economics and is now a master’s student in Computer Science, indicated the critical need for a deep understanding of machine learning methods (letter attached), which will be covered by the MS in DS but not covered in current non-CS graduate certificates.

Our contact with our alumni and students in computer science/statistics/mathematics/specific disciplines resulted in the same message: The MS-DS degree is greatly needed and sought after by students locally and regionally. We sent out a survey to our alumni and students in the Departments of Computer Science, Mathematical Sciences, Biology, Public Health, and Economics, asking them about their feedback about a master’s program in Data Science. We sent the survey to 437 students (267 current students and 170 recent alumni). The survey was sent out on December 1st, 2018, and results collected on December the 15th, 2018. Among the 135 who responded to the survey, 97% noted that Data Science was an important area (see Figure 1), 97% believed a degree in Data Science will improve their employment prospects (see Figure 3), 100% of participants noted that they would recommend a graduate degree in Data Science to those willing to further their careers (see Figure 2), and 97% believed a degree in Data Science will improve their employment prospects (see Figure 3). Of the 135 responses we received, 100% were positive. Of all responses to the question “Would you recommend to those willing to further their careers to pursue a graduate degree in Data Science?”, 29.1% indicated that they would recommend a Data Science graduate degree to someone if they were interested in that area of study, whereas the rest, 70.9%, simply said they would recommend a graduate degree in Data Science, regardless of their interests.

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Figure 1. Responses to the following survey question: Do you find Data Science an important area?

Yes Yes, if they were interested

Figure 2. Responses to the following survey question: Would you recommend to those willing to further their careers to pursue a graduate degree in Data Science?

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Figure 3. Responses to the following survey question: Will a degree in Data Science improve your employment prospects?

We further contacted 3 students randomly selected from a pool of 20 alumni with a focus on fundamentals of data analysis methods (Dr. Rajendra Banjade – now at Amazon, Dr. Archana Bhattarai – now at Apple, Inc, and Dr. Vivek Datla – now at Phillips Research in Cambridge, MA). Dr. Rajendra Banjade, who received his Ph.D. in Computer Science in August 2017, emphasized the importance of Data Science compared to other academic majors in terms of its great applicability and need in many fields (letter attached) in an era in which data is collected and stored in unprecedented volumes. Dr. Archana Bhattarai noted that “in coming 5 years, we will run short in data science resources in the United States.” Dr. Vivek Datla indicated that “many companies across many domains (e.g., logistics, healthcare, pharma, banking, manufacturing, etc.) including ours are eagerly seeking new hires with Data Science background.”.

Not only do our students and alumni express great interest in the MS in DS program, data provided by other universities convey the same message. Many universities already offer programs in Data Science; for instance, there are more than 500 programs listed on the www.datascience.community. Table 1 shows the cumulative growth in the number of applicants to MS in Data Science programs as well as the number of graduates.

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Figure 4. Growth of Analytics and Data Science Master’s degree programs in the United States.

Figure 5. Cumulative master’s degrees awarded in Data Science in the United States.

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Employer need/demand Due to the emerging nature of the Data Scientist profession, the Bureau of Labor Statistics, for instance, does not yet have an entry for it and therefore Data Scientist job demand is not available from federal government sources. Instead, we will report from various sources demand predictions for related jobs.

Local and regional need/demand For local and regional need/demand, as mentioned, we surveyed local and regional institutes and companies. In the Memphis area, we contacted in total 5 organizations including AutoZone, FedEx, International Paper, University of Tennessee Health Science Center, and St. Jude Children’s Research Hospital. These are all well-known large organizations in the Memphis area with a diverse focus from auto component retail chain (AutoZone) to logistics (FedEx) to paper-based products (International Paper) to health-related research and consulting (University of Tennessee Health Science Center, St. Jude Children’s Research Hospital). Among the five organizations we sought feedback from, four responded (AutoZone, International Paper, University of Tennessee Health Science Center, St. Jude Children’s Research Hospital, LeBonheur Children’s Hospital, FedEx) and all were positive and supportive of the MS program. Overall, all the research institutes and companies expressed their high demand and a great need for Data Scientists holding a Master of Science degree in Data Science (support letters from Ron Griffin, SVP/CIO, Customer Satisfaction AutoZone; Dr. Bala Vaidyanathan, Director of Advanced Analytics and Industry Research at Fedex; James Dutkosky, Senior Manager of Information Technology International Paper; Dr. Daniel L. Johnson, Molecular Bioinformatics Core Director and Parya Zareie, Data Manager, at University of Tennessee Health Science Center; and Drs. Li Tang and Hui Zhang, Department of Biostatistics, St. Jude Children’s Research Hospital).

Dr. Zhang noted in his letter the importance of Data Science, “The great progresses in computer science, statistics and data generations during past decades have resulted in a great era of data science. For example, St. Jude Children’s Research Hospital is investing $50 million to build a data center for the 2016-2021 strategy. The new data center, as well as many other St. Jude units, such as the Department of Biostatistics and the Department of Computational Biology, are in great need of data scientists, who must have extensive training in both computer science and mathematics/statistics.” In addition, he noticed the lack of qualified individuals with Data Science skills: “However, the greater Memphis area faces a huge deficit of highly educated experts in data science. In addition, as the president of West Tennessee Chapter of American Statistical Associate, I have extensive interaction with data analysis groups in local industries, such as FedEx, AutoZone, International Paper Inc., Medtronic, etc. I noticed they are facing a similar situation as St. Jude does and are competing with us to recruit qualified data scientists, especially those who received training in database system, machine learning and statistical learning simultaneously.”

For institutes and companies outside Memphis, we focused on a diverse group of companies such as Phillips Research, Audible/Amazon, and Lilly (pharma). Response from Lilly was received, and the feedback is positive. In particular, Dr. Qu mentioned in his letter that “…… The demand for trained expertise in Data Science continues to increase as the world becomes more dependent on large and predictive data and numerical reasoning. As one of the global

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pharmaceutical companies, Eli Lilly recently formed the Department of Advanced Analytics & Data Sciences (AASD) and continues hiring more and more data scientists. As a Data Scientist with Eli Lilly I predict a shortage of Data Scientists will exist for the next decade.”

We also discussed with local employers on numerous occasions, such as during the Memphis DATA conference (www.memphis-data.org), and during meetings with, for instance, the Computer Science Industry Advisory Board members.

The Memphis DATA conference that The University of Memphis organized in March 2018 attracted nearly 200 attendees from the West Tennessee region of which baout 50 were from local companies Many of these individuals were looking for prospective employees and visited the graduate student research poster session.

Below, are testimonials from Computer Science Industry Advisory Board members who are managers and executives at local/regional companies.

“We have strong demand [for] Data Scientists and Data Architects. The demand is strong across all domains, all functional areas, and all operating companies in FedEx. For example, my boss is hiring a director of Data Architecture with [an] entire team of data management folks. The data scientists need to know how to write code, not just using tools. They also need to have a good foundation [in] data architecture discipline. “ FedEx – Xuan Liu

“Yes, we have hired a data scientist in Oxford in the past 2-3 years, and the broader CoreLogic organization has brought in several. I don’t have the numbers of new data scientists hired outside of Oxford off the top of my head, but it is certainly a skill set we recruit for across the organization.” – John Marsalis, CoreLogic/FNC

“We have hired and plan to hire additional candidates that have data science related skills.” – James Dutkosky, International Paper

A quick search in mid-August on the job search website Indeed, showed 54 Data Scientists job openings in the Memphis area and 328 in the state of Tennessee.

In addition to feedback from local and regional employers, we assessed employment data in Tennessee Master level Data Scientists and related jobs such as computer scientists and statisticians. Computer Scientists have an average pay of $114,520 per year according to the Bureau of Labor Statistics (https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information- research-scientists.htm) and according to BLS “Employment of computer and information research scientists is projected to grow 19 percent from 2016 to 2026, much faster than the average for all occupations. Computer scientists are likely to enjoy excellent job prospects, because many companies report difficulties finding these highly skilled workers.”

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Tennessee’s demand for Master level Computer Scientists in May 2017 is higher than, or comparable to, the demand in most States in the U.S as shown in Figure 6. The average pay in TN for this profession is $109,450.

Figure 6. Employment of computer and information research scientists by state.

Statisticians have an average pay of $84,760 and for the period 2016-2026 the “Overall employment of mathematicians and statisticians is projected to grow 33 percent from 2016 to 2026, much faster than the average for all occupations. Businesses will need these workers to analyze the increasing volume of digital and electronic data.”(https://www.bls.gov/ooh/math/mathematicians-and-statisticians.htm) Similarly, as shown in 7 (Bureau of Labor Statistics [BLS], https://www.bls.gov/oes/current/oes152041.htm), Tennessee’s demand for Master level statisticians in May 2016 is higher than or comparable to the demand in most States in the U.S.

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Figure 7. Employment of statisticians by state. Tennessee’s employment is above national average.

While BLS does not yet provide reports on the new profession of Data Scientists, other job websites do. For instance, Glassdoor indicates an average salary of $111,782 for Data Scientists in the Memphis area (https://www.glassdoor.com/Salaries/memphis-data-scientist-salary-SRCH_IL.0,7_IM551_KO8,22.htm). Similarly, according to the 2018 Top 50 best jobs in America report by Glassdoor, Data Scientists are at position #1 (https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm). In fact, for the third year in a row, Data Scientist topped Glassdoor's list as the best job in America. "Data scientist has ruled as one of the hottest jobs for years, proven by its third consecutive No. 1 ranking," according to Glassdoor Chief Economist Dr. Andrew Chamberlain. "This is due to the high demand (4,524 open jobs), the high salary ($110,000 median base salary) and high job satisfaction (4.2/5). Not only are tech companies scrambling to hire data scientists, but industries across the board, from health care to nonprofits to retail, are also searching for this talent." To determine which jobs have the most to offer, Glassdoor looks at the 50 best jobs in America for 2018. Glassdoor generated this ranking by considering earning potential, jobs satisfaction and number of job openings.

Given the potential strength and increasing demand for MS-DS degrees locally and regionally, we further investigated the potential of The University of Memphis offering an MS-DS degree by assessing similar programs in the Tennessee area and its surrounding regions to examine local and regional demands. There are limited formal programs in Tennessee that focus on Data Science.

Lipscomb University in Nashville offers a MS in DS degree: https://www.lipscomb.edu/academics/programs/data-science-graduate . A closer analysis of the courses listed as part of the degree reveals the absence of Machine Learning, a key course offering much

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needed fundamental skills for Data Scientists. Furthermore, they lack the paired (core, domain specific) cluster design that our proposed MS-DS degree offers. That is, they propose a one-size-fits-all training with no domain-specific training on data analysis methods for specific areas. In our design, students will be trained on the fundamentals of Data Science, which are generally applicable to all areas, as part of the core, and then they can choose to go in more depth on Data Science methods specific to certain disciplines such as biology, public health, economics, or business information technology.

Similarly, Vanderbilt University offers a 48-credit hour MS in DS program housed in the Data Science Institute launched in August 2018 (https://www.vanderbilt.edu/datascience/academics/msprogram/admissions/). As with Lipscomb University’s offering, the MS in DS at Vanderbilt does not offer domain-specific Data Science tracks. To our knowledge, we will be the only University in the state of Tennessee with an MS-DS degree that will offer a curriculum that trains students in both the fundamental aspects of Data Science as well as giving students the possibility of specializing in domain-specific Data Science methods. This design will offer students who want to pursue a Data Science career in a particular domain a competitive advantage as they will graduate with domain specific Data Science skills, which programs that follow a one-size-fits all approach cannot offer their graduates at the level that the University of Memphis program will. Our university has strong expertise in the major areas involved in the MS-DS program including Computer Science, Statistics, Public Health, Biology and other socio-behavioral areas, Economics, and Business Information Technology. This provides our The University of Memphis a unique opportunity to offer formalized training in order to meet local and regional needs of Data Scientists with strong analytical skills, establish a solid foundation for new career options in various areas, and prepare graduate students to pursue subsequent Ph.D. studies in Data Science.

The courses are carefully selected to cover computer science topics such as machine learning and databases, statistics topics such as statistical theory, classical statistical analytical methods, statistical learning, Bayesian methodologies that are specifically tailored and applicable to analysis of big data, and provide a thorough training in domain specific data analysis methods and their applications. Students completing this MS program will be competitive for a wide number of positions in government and the private sector.

Future sustainable need/demand The job market for Data Scientists and related professions is growing fast. We report on job outlook of related professions due to the lack of information from the Bureau of Labor Statistics (BLS) on the new profession of Data Scientists, as already noted. Nevertheless, organizations such as Glassdoor (glassdoor.com), the McKinsey Institute, and other organizations provide continuing analysis of labor market trends.

According to the Bureau of Labor Statistics (BLS) the Data Science related professions like statisticians and computer scientists are among the ones with the highest growth outlook for the period 2016-2026 (https://www.bls.gov/ooh/fastest-growing.htm).

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Indeed, the BLS predicts much faster than average growth for statisticians and computer scientists for the period 2016-2026. There will be a 33 percent growth from 2016 to 2026 for biostatisticians and a 19% growth for Computer Scientists. The number of statisticians at the Master level was 37,200 in the year of 2016, and by 2026, an increase of 12,600 is expected. BLS notes that “Job opportunities are expected to be favorable for those with very strong quantitative and data analysis skills. Computer programming skills will remain important to many employers, as will be keeping up with new statistical methods and programming languages.” Our MS-DS program will offer both strong programming and statistical methods training thus giving our graduates a competitive advantage. Furthermore, BLS notes that “in addition to technical skills, applicants with strong communication skills and the ability to interpret and present their data and findings will have stronger job prospects.” Accordingly, our MS-DS program will emphasize data interpretation and communication skills.

Similarly, the number of Computer Scientists in 2016 was 27,900, and by 2026 it is expected an increase of 19% or 5,400. Interestingly, BLS notes that Computer Scientists “seeking employment in a specialized field, such as finance or biology, knowledge of that field, along with a computer science degree, may be helpful in getting a job.” Our MS in DS program design addresses precisely this domain knowledge need beyond core Data Science skills applicable to all domains.

It is important to mention that there are other Data Science related jobs that BLS reports on such as Database Administrators. While it is beyond the scope of this degree proposal to provide an exhaustive account of related jobs, BLS reports that employment for Database Administrators are growing at comparable rates.

More up-to-date analyses and estimates for the labor market like the recent study by Mckinsey Institute states that "a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.)." There is a significant demand for experts in industry, government, education, healthcare, etc., that have requisite skills to collect, process, and analyze data. Further, the report also states that there would be four to five million jobs in the U.S. requiring data analysis skills by 2018.

The McKinsey Institute states that “significant constraint on realizing value from Big Data will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning,” and warned of a shortage of more than 1.5 million managers and analysts who can use the analytical output of Big Data for Decision-making (http://www.mckinsey.com/business-functions/digitalmckinsey/our- insights/big-datathe-next-frontier-for-innovation).

According to Glassdoor.com, “data scientist” was the number 1 job in America in 2016, 2017, and 2018. However, filling these new jobs requires re-training personnel whose primary expertise may be in varied domains such as hard sciences, business, social sciences, etc., to be ever more data-savvy. A Garner study recently reported that “The global population of chief data officers (CDOs) has grown 100-fold, to 10,000 over the past decade as enterprises around the world race to exploit their data reserves.”

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There is clearly a human expertise bottleneck when it comes to Data Science and in particular when it comes to processing large datasets of varying types using massive computational resources. While we can scale data collection and processing, we cannot scale human expertise without a strategic, sustained, and concerted effort by all stakeholders. Universities in particular, through programs such as the one proposed here, could address this expertise bottleneck.

Figure 5, from the Institute for Advanced Analytics, suggests almost exponential growth of the cumulative number of Data Science master’s degrees. Extrapolating into the foreseeable future, we anticipate this growth to continue for some time.

PROGRAM COSTS/REVENUES The budget includes salary for the Program Director who will run the program. The director will be in charge and supervise all aspects of the new MS-DS program including advertising, recruitment, application, admission, and student advising processes, will work closely with other departments and faculty to schedule courses, update curricula, advise and mentor students, and further develop the program as needed. Furthermore, the director will supervise the half-time administrative assistant and half-time tech support hire. The salary line for the Director will be supplementary compensation for release time from other activities, and it is not a full time position.

No new courses or additional faculty are required. We do request the equivalent of two additional faculty lines in order to support the expected growth in enrollment for the core courses. One of the faculty lines will be devoted to CS core courses upon start up and one in Year 3 when we expect to also have a full online version of the MS-DS degree.

As noted earlier, the plan is to offer both on-the-ground and online versions of the MS-DS programs. By Spring 2020, 4 of the courses in the proposed MS-DS degree will be available online. We will develop at least 6 additional online versions of existing courses in order to offer the whole MS-DS degree online. This will be done in the during the first 3 years such that in year 4 current and entering students may opt for the fully online MS-DS degree. This will run in parallel with the on-the-ground degree. We conservatively expect to have 10 online students in year 4 and 20 in year 5. In order to cope with project enrollment growth, 2 faculty lines in Data Science to help teach the core courses, e.g., Machine Learning and Fundamentals of Data Science, and selected electives. The costs associated with the faculty lines are not shown in the budget as these lines will be allocated through replacement of retiring faculty lines to the MS-DS program. The MS-DS faculty lines will have duty such as advising and administrative tasks allocated to the MS-DS program. All faculty teaching the core courses will have to dedicate time for advising and other administrative tasks such as curriculum development in the MS-DS program. Their corresponding home department will have to release some of their time accordingly. Potential revenues are clear (see proposed budget/financials attached).

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Support (stipends and tuition) have been included in the budget for 6 graduate assistants (GAs). The GA support will help us attract high-quality talent to Memphis area. Furthermore, GAs will help run the program, e.g., some faculty, the program director, and the admin assistant will need extra help that a GA could offer on a limited basis. GAs will be allocated to faculty teaching core courses in Data Science and also to those who teach the largest elective classes.

We also budgeted for one-time new/renovated computer lab space and corresponding equipment. We will rely on publicly available software platforms and those currently in-hand. We have requested and allocated funds for cloud computing and storage as students will need to be able to conduct big data analyses using millions of computers in the cloud.

The budget includes operating funds for travel (invited speakers, recruiting events, accreditation costs when needed), advertising, and software and cloud computing.

Revenue projections include tuition and fees, potential research and grant activity, expected gifts, and any other expected revenues.

THEC FINANCIAL PROJECTION FORM See Appendix A for the completed THEC Financial Projection Form

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REFERENCES Berman, F., Rutenbar, R., Hailpern, B., Christensen, H., Davidson, S., Estrin, D., Franklin, M., Martonosi, M., Raghavan, P., Stodden, V., Szalay, A.S. (2018). Realizing the Potential of Data Science, Communications of the ACM, April 2018, Vol. 61 No. 4, Pages 67-72

Brennan, P. & Bakken, S. (2015). Nursing Needs Big Data and Big Data Needs Nursing. Of Nursing Scholarship, 4/5:477-481.

Cao, L. (2017). Data Science: A comprehensive overview. ACM Comput. Surv., 50, 3, Article 43 (June. 2017), 42 pages.

Donoho, D.L. (2000). High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality. Lecture Delivered at the “Mathematical Challenges of the 21st Century” Conference of the American Math. Society, Los Angeles.

Frakt, A.B. & Pizer, S.D. (2016). The promise and perils of big data in healthcare. Am J Manag Care, 2016, 22(2):98-9.

Kirkpatrick, K. (2019). Technologizing Agriculture, Communications of the ACM, February 2019, Vol. 62 No. 2, Pages 14-16.

Quemy, A. (2017). Data Science Techniques for Law and Justice: Current State of Research and Open Problems, Proceedings of the European Conference on Advances in Databases and Information Systems ADBIS 2017: New Trends in Databases and Information System, pp 302-312.

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APPENDIX A: THEC Financial Projections Form

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Year 1 Year 2 Year 3 Year 4 Year 5

I. Expenditures

A. One-time Expenditures

New/Renovated Space - Lab $140,000 $ - $ - $ - $ -

Equipment - Computers 40,000 - 40,000 -

Library - - - -

Consultants - - - - -

Travel

Other -

Sub-Total One-time $180,000 $ - $ - $ 40,000 $ -

B. Recurring Expenditures

Personnel

Administration

Salary - Faculty Program Director $ 35,000 $ 36,500 $ 37,132 $ 38,245 $ 39,393

Benefits - Faculty Program Director 12,000 12,360 12,731 13,113 13,506

Sub-Total Administration $ 47,000.00 $48,860.00 $ 49,862.30 $ 51,358.18 $ 52,898.92

Faculty

Salary - - - - -

Benefits - - - - -

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Sub-Total Faculty $ - $ - $ - $ - $ -

Support Staff, admin

Salary - 1/2 time $ 25,000 $ 25,570 $ 26,523 $ 27,318 $ 28,138

Benefits - 1/2 time 10,000 10,300 10,609 10,927 11,255

Support staff, tech

Salary - 1/2 time 25,000 25,570 26,523 27,318 28,138

Benefits - 1/2 time 10,000 10,300 10,609 10,927 11,255

Sub-Total Support Staff $ 70,000 $ 71,740 $ 74,264 $ 76,490 $ 78,786

Graduate Assistants (research assistants)

Salary - 6 students $ 81,000 $ 83,430 $ 85,933 $ 88,511 $ 91,166

Benefits - 6 students 1,539.00 1,585.17 1,632.73 1,681.71 1,732.16

Tuition and Fees* (See Below) 44,040 44,040 44,040 44,040 44,040

Sub-Total Graduate Assistants $157,440 $ 160,842 $ 164,346 $167,955 $171,673

Operating

Travel $ 7,500 $ 7,725 $ 7,957 $ 8,195 $ 8,441

Software and cloud computing 25,000 25,000 25,000 25,000 25,000

Equipment - - - - -

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Marketing Flyers, Brochures, Ads 20,000 10,000 10,000 5,000 5,000

Sub-Total Operating $ 52,500 $ 42,725 $ 42,957 $ 38,195 $ 38,441

Total Recurring $296,079 $292,380 $298,688 $300,276 $307,064

TOTAL EXPENDITURES (A + B) $476,079 $292,380 $298,688 $340,276 $307,064

*If tuition and fees for Graduate Assistants are included, please provide the following information.

Base Tuition and Fees Rate $ 7,340.00 $ 7,340.00 $ 7,340.00 $ 7,340.00 $ 7,340.00

Number of Graduate Assistants 6 6 6 6 6

Year 1 Year 2 Year 3 Year 4 Year 5

II. Revenue

Tuition and Fees1 440,400 660,600 880,800 880,800 880,800

Institutional Reallocations2 11,540 (351,433) (564,371) (561,801) (554,002)

Federal Grants3 - - - - -

Private Grants or Gifts4 55,000 15,000 15,000 55,000 15,000

Other5 - - - - -

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BALANCED BUDGET LINE $476,079 $292,380 $298,688 $340,276 $307,064

Notes:

(1) In what year is tuition and fee revenue expected to be generated and explain any differential fees. Tuition and fees include maintenance fees, out-of- state tuition, and any applicable earmarked fees for the program.

Tuition will be generated by 20 full-time and 20 part-time students in the first year, 30 full- time and 30 part-time in the second year, and 40 full-time

and 40 part-time in the remaining years.

(2) Please identify the source(s) of the institutional reallocations and grant matching requirements if applicable.

Paying extra compensation to a faculty for program director services, marketing flyer production and distribution.

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(3) Please provide the source(s) of the Federal Grant including the granting department and CFDA (Catalog of Federal Domestic Assistance) number.

None involved.

(4) Please provide the name of the organization(s) or individual(s) providing grant(s) or gift(s).

Requesting donated computers and software.

(5) Please provide information regarding other sources of the funding.

None involved.

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APPENDIX B: Letters of Support

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