Data scientists are in high demand as the use of Big Data becomes increasingly important to the private and public sectors. In 2011, the McKinsey Global Institute predicted “exponential growth in data for the foreseeable future.”
This prediction has come to pass along with a subsequent shortage of professionals trained to work with large data sets. Forbes quoted tech expert Tom Groenfeldt in 2012 as saying that insiders consider “the combination of skills across computing, math, statistics and business” to be “pretty rare.”
In North Carolina, the Triangle is a hotbed of data science activity. In 2011, the Bay Area Council Economic Institute used US Bureau of Labor Statistics to identify the top 25 metropolitan areas in the country with the highest concentration of technology jobs in its Technology Works report. Both Durham-Chapel Hill and Raleigh-Cary made this list.
The environment for data scientists and other tech workers in the Triangle has only grown since then, and Mashable listed this region of North Carolina to be the 3rd most likely area in the country to become the next Silicon Valley in a 2015 article.
The Triangle lives up to this prediction with hundreds of companies in data science and analytics. Thousands of data professionals and tech experts work in this part of North Carolina. Prominent data science companies in the area include two companies using Big Data to improve healthcare. One is Durham’s Validic—a company that uses the cloud to provide data services and integrations for the healthcare industry.
Charlotte boasts Premier, Inc., previously the Premier Healthcare Alliance—a purchasing group for thousands of hospitals and tens of thousands of non-acute sites. Premier’s CTO, Denise Hatzidakis, told Forbes in 2012 that the group entered into an alliance with IBM to analyze the massive amount of data collected from members. She also reported that preliminary studies indicated that improvements in utilizing the data could save $4.5 billion and 70,000 lives.
North Carolina residents who want to take advantage of the opportunities offered by the state’s data science companies have a wealth of high-powered educational options to obtain a master’s degree to enter this lucrative field.
Preparing for a Master’s Degree in Data Science in North Carolina
Students who want to become data scientists should begin to prepare for a master’s degree during their undergraduate Bachelor’s of Science studies. Obtaining relevant work experience and taking the appropriate courses will greatly improve their chances of being accepted into a data science master’s program.
Undergraduate Degree and Master’s Prerequisite Courses
Graduate schools that offer data science programs seek students who have the appropriate background for this field. Such preparation entails:
- Obtaining a Bachelor’s of Science degree in a quantitative field such as computer science, statistics, applied math, or engineering
- Taking courses in key disciplines such as calculus I and II, linear algebra, statistics, quantitative methods, and programming languages
- Having a minimum GPA of 3.0
Relevant Personal and Work Experience for Admissions
Typically, graduate schools seek applicants with highly relevant professional experience:
- At least five years of technical work experience ideally through employment that demonstrates quantitative skills
- Personal experience related to data mining, database administration, coding, hacking, programming, mathematics, or statistics
- Strong communication skills
Examples of qualifying local experience in North Carolina that may satisfy these requirements include:
- IT Senior Application Architect with Price Waterhouse Cooper
- Technology Development Program Associate with UnitedHealthGroup
- Global Big Data Engineer with Lenovo
- Database Engineer with ChannelAdvisor
- Principle Software Engineer/Developer with Fidelity Investments
Performing high quality work with an employer is crucial to obtaining the stellar letters of recommendation often required for admission into a data science master’s program.
Preparing for Success on the GRE/GMAT Exams
Obtaining a score in the top 15th percentile of the GRE and/or GMAT is an excellent way to demonstrate core competency in the skills in key data science areas. It is essential to prepare for these exams ahead of time, and both students who have taken the exams and the testing services themselves recommend taking practice tests on sample math problems until the candidate is highly comfortable with them.
The GRE’s quantitative section is particularly important and evaluates the candidate’s skills in data analysis, algebra, geometry, and arithmetic. Candidates seeking a career in data science should pay particular note to statistics including standard deviations and probabilities. Sample questions and free practice exams are available at the official GRE website.
The General Management Admissions Test (GMAT) evaluates a candidate’s quantitative, writing, and verbal abilities. Graduate school admissions departments expect high scores in all of these areas. However, the 37 questions that assess data efficiency and problem solving are particularly important. Candidates can take GMAT practice exams through Veritas Prep and The Princeton Review®.
Filling Gaps in Functional Knowledge Through MOOCs and Bridge Courses
Massive Open Online Courses (MOOCs) – If a candidate has not been trained in key skills during his or her education or experience, Massive Open Online Courses (MOOCs) are one way to acquire these skills. Such courses are educational programs hosted online designed to supplement the education required to become a data scientist. While many online hosts offer MOOCs, Class Central is a course that is particularly apt for data scientists wishing to supplement their education.
Bridge Programs – Many graduate programs offer bridge programs designed to enable candidates to supplement their skillsets in areas that apply to data science. Two types of bridge programs are available:
- Fundamental bridge programs – courses in algorithms and their analysis, data structures, and linear algebra
- Programming bridge programs – training in such essential programming languages as JAVA, C++, and Python
Earning a Master’s Degree in Data Science in North Carolina
Prospective data science students in North Carolina have a wealth of option between the high quality online schools available and local data science programs in the Triangle.
With the prominence of the Triangle in the competitive business of data science, universities in the area offer high-powered master’s degrees to provide the technical and theoretical skills for students to enter this lucrative workforce.
On-campus Data Science Programs Available in North Carolina
Several universities located in the Triangle offer a variety of specialized data programs that enable prospective students to choose the program best suited to their career goals. On-campus graduate programs available in North Carolina include:
Data Science Initiative collaboration between the Colleges of Business, Computing and Information, and Health and Human Services
- Professional Science Master’s (PSM) in Data Science and Business Analytics
- Leads to an M.S. in Data Science and Business Analytics (MSBA)
- Professional Science Master’s (PSM) in Health Informatics
- Graduate Certificate in Data Science and Business Analytics
- Graduate Certificate in Health Informatics
Institute for Advanced Analytics:
- M.S. in Analytics (MSA)
- M.S. Program in INSTORE (Interdisciplinary Statistics and Operations Research)
- Machine Learning
- Business Analytics
- Computational Finance
Features of North Carolina’s Online Data Science Master’s Programs
The focus of the graduate data science programs in North Carolina’s state schools vary depending on the career goals of their applicants.
Charlotte – Professional Science Master (PSM) Degree Programs
Professional science master’s degrees differ from traditional master’s degree in two ways. One is the program’s practicum or internship requirement that connects the students with industry leaders. The other is the presence of an advisory board that contains business and industry executives.
PSM. in Data Science and Business Analytics (DSBA) – With its interdisciplinary intersection of computer and information sciences, business, statistics, and operations research, graduates from this professional program are well equipped for employment in a number of data science industries. This programs leads to an M.S.
PSM in Health Informatics – With a healthcare revolution utilizing Big Data taking place, the PSM in health informatics is designed to produce professionals with the skills in data science to work with large data sets and who understand the language of health care.
Raleigh – MS in Analytics (MSA)
This master’s degree equips students with skills in data modeling and visualization, data cleaning, statistics, computer programming, and industry-standard analytical skills. The culmination of this master’s degree is its eight-month Practicum in which teams of 4-5 students conduct real-world analytics using data from any one of a number of different industries.
Chapel Hills – MS in Interdisciplinary Statistics and Operations Research (INSTORE)
The Machine Learning track of this master’s programs exposes students to rigorous courses in both statistics and optimization, so that graduates excel in the analysis of complex sets of data. In addition to the coursework required for the degree, students can specialize by taking courses from departments such as Genomics, Bioinformatics, Economics, Computer Science, and Biostatistics.
Online Data Science Programs For North Carolina Residents
In addition to the data programs offered by state schools in North Carolina, students have a number of options to obtain a master’s in data science from highly respected online programs.
Such programs offer greater flexibility to working professionals and are offered in a variety of options ranging from full-time and part-time to accelerated programs. The program lengths range from 32 months for students attending part-time to 18 months for full-time students. Accelerated options can be completed in as little as 12 months.
While the initial coursework is entirely online, most programs require an immersion experience in the final semester. Students take intensive classes on campus and interact with their professors and peers during this final semester.
Degree programs available include:
- Master of Science (MS) in Data Science
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MSDS)
- Graduate Certificate in Data Science
- Online Certificate in Data Science
- Data Science Certificate
- Data Mining and Application Graduate Certificate
Core Curriculum Content
The coursework will vary in different Master’s programs, but the core courses will cover essential skills that data science positions require. All programs will include these topics:
- Machine learning and artificial intelligence
- Data storage and retrieval
- Data research design and applications
- Data mining
- Data research design and applications
- Scaling data – macro and micro
- Network and data security
- Statistical sampling
- Experimental statistics
- Applied regression and time series analysis
- Experiments and casual inference
- File organization and database management
- Information visualization
- Quantifying materials
- Advanced managerial economics
- Ethics and law for data science
Most online data science programs provide an opportunity for the students to apply their theoretical training to real-world problems in an immersion experience. This enables students to work in small teams and spearhead a data science project.
Key Competencies and Objectives
Data science master’s programs equip their graduates with a wide array of proficiencies in core areas. This breadth of training will enable these data scientists to work in a number of core areas:
- Data mining and machine learning
- Data and network security
- Data collection and analysis
- Data cleansing
- Statistical sampling
- Research design
- Database management and file organization
- Communication and visualization
- Programming languages such as Python and C++
- Ethics, privacy, and relevant law
Career Opportunities for North Carolina Data Scientists with Advanced Degrees
North Carolina’s increasing prominence in high-tech industries provides a number of options for data science employment. The Triangle in particular had a strong focus in tech for decades and in recent years became a magnet for data centers that require data scientists with advanced degrees.
From the creation of SAS® software years ago to the recent opening of MetLife’s global technology and operations headquarters, the Triangle continues to draw cutting edge data science companies including Ipreo Holdings and Evalueserve, both of which provide data and technology solutions and market intelligence to corporate professionals and financial services firms.
Graduating with a master’s degree will give data science students the opportunity to utilize their academic training to its full extent in one of North Carolina’s many data science companies or in its public sector. Shown below are job listings for data science positions in North Carolina that were compiled in March 2016. These listings are informational only and meant to showcase the variety of data science job options in North Carolina. They should not be construed as current job offers or an assurance of employment.
Senior Data Scientist–Econometrics with MaxPoint in Morrisville – This professional must have a deep knowledge of numerical and statistical packages such as Numpy, Pandas, Sklearn, and R. The position also requires writing complex database queries using Hadoop, Spark, Impala, and MapReduce to establish links between large datasets. Applicants must have an advanced degree in a quantitative field such as statistics, mathematics, operations research, or econometrics. In addition, the position requires 3 years of experience in the required areas and 10 years of career experience preferably at startup or small- to mid-sized software development companies.
Data Scientist with Cognizant in Charlotte – The position requires that applicants understand machine learning, predictive modeling, statistical analysis, and conceptual modeling. Applicants must have extensive technical knowledge in Hadoop, Samza, Spark, .Net framework, Java platform, and infrastructure architecture. Cognizant prefers applicants with a masters in applied mathematics, statistics, or engineering and requires 8 years of technology experience with 3+ years of data science experience.
Data Scientist – IT Analytics with SAS Institute in Cary – This position requires programming skills with SAS knowledge, scripting languages, multiple operating systems, and the knowledge to deal with large volumes of data. Applicants must have a master’s degree in applied mathematics, statistics, or a related quantitative field and 3-5 years of experience in building analytical models or data analysis.