Not all Master’s Degrees in Data Science are created equal…
Big Data and Data Analytics are revolutionizing all industries, and the demand for skilled employees continues to grow. In fact, in a recent report, IBM projects that demand for Data Science Analytics (DSA) skills across all job categories will soar 15% by 2020. The sectors leading this demand are Finance and Insurance, Professional Services, and IT, totaling 59% of the projected DSA job market.
Data science opportunities have emerged from an organization’s need to use the deluge of data to improve both internal resources as well as external interactions with customers and suppliers. Employers, especially in the aforementioned sectors, see a correlation between data and sound business decisions that lead to profitability. Therefore, specialists who can collect, manage, use, and describe data to help drive decisions and strategy are integral to a company’s ongoing success.
Employers look to academia to produce the specialists they need. With that in mind, we will examine advanced degrees that offer new and significant opportunities in the DSA market.
When thinking of graduate studies, there are three categories in which data-focused master’s degrees can be examined -- MBA with a concentration in Data Analytics, MS in Business Analytics, and MS in Data Science. There is no “best” degree; the most appropriate degree depends entirely on what aspect of data you are most interested in tackling, and what function within an organization you envision filling.
Broadly, I’ve examined the three master’s degrees individually and the career paths they are most suitable for. The aim of each of these degrees gives the necessary tools to succeed in these emerging career paths.
Who will lead the team that analyzes the data?
A Masters in Business Administration (MBA) prepares its graduates to handle all aspects of a business from a macro perspective. A typical 2-year MBA commences with theoretical study followed by a praxis of some kind, giving its students both theory and hands-on training.
Answering to employer demands for data-driven MBAs, b-schools have developed data-focused curriculums with a concentration in Data Analytics. Typically, an MBA, including concentrated degrees, will be the decision makers, those looking at strategy and development from a macro-perspective. An MBA with a concentration in Business Analytics can be used in a variety of different fields, where data can help build strategy that leads to optimal profitability.
A number of universities offer MBA’s in Business Analytics; I have outlined only three (not ranked).
NYU Stern School of Business launched an MBA with a concentration in Business Analytics, that is “especially applicable to careers in consulting, finance, and marketing.” Students learn how models and data can be used to support business decisions. NYU Stern graduates with an MBA in Business Analytics have worked in consulting firms like Bain, BCG, and Deloitte; in finance, like Rothschild, HSBC, and Amex; and also in marketing for companies like Johnson & Johnson, Bayer, and Estee Lauder. About 97% of MBA graduates received an offer of employment within three (3) months of graduation. Graduates have secured management positions in Consulting and Investment Banking in Finance, making up 64% of accepted offers.
University of Pennsylvania’s Wharton School of Business also offers a 20-month MBA with a concentration or “major” in Business Analytics. The in-depth technical training enables students to use and oversee the use of data when forming inferences and predictions so they can make sound data-driven business decisions. Students can structure their degree so that, at the end of their 20-month Wharton experience, they leave with an MBA with two majors. Selecting from 19 possible choices, students have the option to graduate with an MBA in Business Analytics and Finance, or Business Analytics and Entrepreneurship & Innovation, or even Business Analytics and Strategy & Economics—about 40% of Wharton’s MBA students graduate with two majors.
About 97% of their full-time MBA students seeking employment received job offers. Names that appear on the employer roster include IBM, McKinsey, Amazon, Apple, and Google. Financial Services and consulting are the two predominant industries employing Wharton’s graduates, totaling 61% of the class of 2017. Consulting/Strategy is the principal job function (about 32%).
The University of Notre Dame also offers an MBA with a concentration in Business Analytics, a two-year degree at Mendoza College of Business. The program’s structure enables students to select a concentration after only one semester of core coursework. The curriculum focuses on quantitative techniques, including data mining, statistical modeling, optimization, and project management.
Deloitte, Deutsche Bank, IBM, and Microsoft are some of the leading companies that have hired Notre Dame’s MBA graduates. Of the students seeking employment, about 91% received job offers. Tech and Financial Services have been the leading sectors, with Finance/Accounting (~31%) and Marketing/Sales (~23%) being the prominent job functions.
An MBA in Data Analytics will produce a thought leader with technical skills to collect, manage, oversee, use, and describe data to support business decisions. They learn quantitative skills like data mining, statistical modeling, optimization, multi-objective decision making and project management, all with the aim to solve business problems. The job functions they predominantly occupy remains in the realm of management in finance, accounting, and marketing. Unlike the Masters of Science in Business Analytics, an MBA in Data Analytics learns how to use data without necessarily working on complex modeling.
Quants are welcome
A Master of Science in Business Analytics (MSBA) bridges business and analytics. If we think of the MBAs as the decision maker whose primary training remains in the realm of business administration, then the MSBA will have a deeper understanding of the data helping the MBAs make those data-driven, strategic decisions. A person holding an MSBA will often be employed in technical roles, making IT-related recommendations, and offer data-driven solutions – they look at historical data for new perspectives, giving actionable intelligence.
Aside from being a more data-driven program, the benefits of enrolling in an MSBA include fewer semesters to complete (typically one year) and a lower cost of attendance. People who consider an MSBA are those with experience who want to increase the data use within their existing firms, as well as those with an undergraduate degree in IT, engineering, or tech, seeking to expand their breadth of knowledge in the application of analytics in business. The MSBA’s offer a data-intensive curriculum suitable for data-driven minds.
An MSBA is gaining traction, so there will be a number of program options available. Here are some institutions and programs worth considering (again, not ranked).
The MIT Sloan School of Management offers a one-year Master in Business Analytics (MBAn) for those with ambitions for a career in data science. The program aims to train its students to use, understand, and navigate the diverse datasets enabling them to transform business decisions. Courses the likes of “The Analytics Edge,” “Machine Learning,” and “From Analytics to Action” are a part of the core curriculum. The program culminates with the required Analytics Capstone, a two-person team project working directly with sponsoring/”host” organizations over a period of seven (7) months. The final report and presentation of the project awards a student the formal degree. The “host” organizations represent industry giants like GE Appliances, GroupM, McKinsey, and Nordstrom.
The University of Texas at Austin, Texas McCombs Masters in Business Analytics (MSBA) is a STEM-certified 10-month program. This MSBA appeals to candidates seeking an advanced degree in Business Analytics without necessarily having prior work experience (55% of students have less than 1-year work experience). Predominantly, students pursuing an MSBA have undergraduate degrees in engineering, business, and science, and go on to work in sectors like consulting (33%) and tech (28%). Data Analytics (63%), whether direct hire or consultant, is the principal job function, and graduates go on to work for industry leaders like Dell, Indeed, IBM, PwC, Facebook, and Deloitte.
For the experienced professional who is seeking a quant and technical edge in their existing career, NYU - Stern Masters of Science in Business Analytics (MSBA) may be the right program. The one-year, part-time program is geared towards those looking to add business analytics to their portfolio of knowledge and are comfortable with “synchronous” (in-person) and “asynchronous” (online) style of learning. Its students are required to attend five (5) in-class sessions on NYU Stern’s New York campus, and two rotating global locations (Shanghai and London were 2018’s in-class session worldwide locations). Alumni of this program work in a variety of fields, with a significant concentration in financial services, IT, and retail & hospitality.
Unlike an MBA with a Concentration in Business Analytics, an MSBA digs deeper into the wealth of data enabling them to make sound recommendations and decisions. Their understanding of data can affect how companies design and operate systems to deliver primary products and services. Data can also affect external factors like understanding how companies use social networks, client’s perception of their services, leveraging crowds, etc. An MSBA is an integral part of making those sound decisions. For that reason, MSBA’s will hold positions in consulting and tech. MIT’s MBAn applicants, for example, have more than doubled since the program’s inception in 2016 (from 300 to 800 applicants). The prestige of the university is almost secondary to the importance of such training within the business world.
The Mad Scientist…
Although the MSBA’s and a data scientist’s job functions intersect, the most central distinction between the two is the way they use data. While an MSBA uses historical data to make recommendations, a data scientist needs to write new queries in an attempt to forecast the unknown. Phil Simon, a professor at W. P. Carey Business School at Arizona State and an award-winning author of eight (8) books on tech and our relationship with it, distinguishes the function of the Data Scientist. He describes the Data Scientist as one who “design(s), develop(s), and deploy(s) algorithms through statistical programming that support business decision-making tools.” They use statistical programming language (SAS, SQL, R, SPSS, Python, and Knime) to “create the function of analysis” that enables them to discover opportunities in datasets. In other words, a Data Scientist builds models and conducts experiments to find the most advantageous solutions for business problems.
The functions of the two – MSBA and Data Scientist – are not in direct competition, nor is one in a superior hierarchical bracket than the other. They are the backbone for backward and forward-looking analysis, finding new perspectives on existing problems, and analyzing data allowing them to predict any future issues that new decisions might bring to play. A Data Scientist will hold titles like Data Scientist, Research Scientist, Engineer, and Machine Learning Engineer. These are the most technical of the three DSA-type job categories.
Below are some Data Science master’s programs you should be looking at, if this is a field you are considering (again, not ranked).
Carnegie Mellon’s 16-month master’s degree in Computational Data Science (MCDS), taught by faculty from the Carnegie Mellon’s Computer Science Department and Machine Learning Department, trains students “in all aspects of design, engineering and deployment of very large information systems.” Students are required to declare a major in either Systems, Analytics, or Human-Centered Data Science, which governs the coursework for the entire program. Carnegie Mellon boasts of having a 97% employment rate within 3-month of graduation (academic year 2014/2015). Employees have gone to work for companies like Google, Apple, LinkedIn, and Bank of America. MCDS students hold positions as software engineers, data scientists, and project managers.
Through the Data Science Institute (DSI), Columbia University also offers a 16-month Master of Science in Data Science (MSDS) degree. The MSDS program integrates all top-ranked programs within the university, including Engineering, Medicine, Law, and Humanities giving students a broad perspective on the relationship between data and the real world. In the elective portion of the program, students have the option customize their learning by integrating fields (“verticals”) within their study. The five (5) “verticals” include Cybersecurity, New Media, Financial Analytics, Health Analytics, and Smart Cities. In conjunction with the capstone project, the verticals help students learn how various sectors look at and use data.
Nearly 100% of DSI graduates have obtained job offers within three (3) months of graduation, working for companies like Facebook, Amazon, Google, IBM, and McKinsey, and holding appointments like Data Scientist, Analyst, and Statistician.
New York University (NYU) Center for Data Science offers a two (2) – year Master of Science in Data Science, a highly selective program for students with a strong background in mathematics, computer science, and applied statistics. Like other similar programs, NYU’s MSDS degree culminates with a capstone project where a student collects and processes real-world data, then designs and implements a solution to a problem. Students also have the option to pursue a tracked degree, where one aspect of data-usage takes focus. The available track-routes include General Data Science, Big Data, Mathematics and Data, Natural Language Processing, Physics, and Biology. About 80% of the incoming class of 2017 pursue track degrees in Big Data (~56%) or general Data Science (~24%).
MSDS graduates of 2015 have had a 100% placement rate upon graduation, holding appointments the likes of Data Scientist, Research Scientist, Software Engineer, and Machine Learning Engineer in Tech (45%) and Finance (37%) sectors.
The evolution of tech has impacted the way businesses collect and use data, and specialists in Data Science are integral to the movement. PwC forecasts that by 2020 there will be 2.7M Data Science job postings. Most of the hires will be in categories of jobs occupied by MBAs with a concentration in Business Analytics and MSBA’s; however, Data Scientist and Data Engineers will be the fastest growing occupations with a 40%, five (5) year projected growth rate.
The MBA in Business Analytics and the MSBA will often work hand-in-hand, as one needs the expertise of the other to work out and drive decisions. The MSDS is almost another breed altogether. She is the scientist, the researcher, and the engineer who performs deep-dive investigations into operational efficiencies and implementation research that will affect the direction of the business. Organizations with a strong research department, especially in Finance and Tech, will hire Data Scientists before hiring an MBA in Data Analytics or an MSBA.
Leave a comment below. Let us know where you fall in these categories and your thoughts on the future of data, business and education.
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