In 2012, FCW reported that the city of Memphis, Tennessee was using big data to fight crime. After the Memphis Police Department launched the Blue CRUSH (Crime Reduction Utilizing Statistical History) initiative in conjunction with the University of Memphis, violent crime in the city was reduced. The initiative allows law enforcement officers to draw a polygon around areas of Memphis on a map and to receive predictive information on the likelihood of specific types of crime occurring in that area. This allows certain types of crime to be prevented.
- Syracuse University - M.S. in Applied Data Science: GRE Waivers available
- SMU - Master of Science in Data Science - Bachelor's Degree Required.
- UC Berkeley - Master of Information and Data Science Online - Bachelor's Degree Required.
- Syracuse University - Master of Information Management Online
- Maryville University - Master of Science in Business Data Analytics
- Villanova Business - Master's in Analytics and Study Data Mining, Predictive Analytics Online
Tennessee’s health researchers are also benefiting from big data. In 2014, the National Science Foundation supported a bioinformatics professor at the University of Tennessee working with a team from Washington State University on a $1.3 million grant for the Data Infrastructure Building Blocks (DIBBS) program. This program is designed to build upon and enhance the capacity of genomic databases in processing, managing and exchanging big data.
Clearly, Tennessee’s business and scientific professionals recognize the potential of big data. Bachelor’s-educated professionals with a background in quantitative knowledge and skills are pursuing graduate degrees in data science in Tennessee and online to become part of this revolution. Those who do find that Tennessee offers them many and varied career opportunities.
Information technology consulting and solutions firm Zycron, headquartered in Nashville, is one example of a Tennessee company hiring data scientists. Here, data scientists work with a variety of clients in communicating quantitative analysis to others clearly. They also collect new data, refine existing data, perform hypothesis testing, work on pattern classification, perform parameter estimation, and write and test software in many languages.
Healthcare business services and technologies companies such as Intermedix, which has facilities in Nashville, also use data scientists extensively. Data scientists at Intermedix build and enhance products for current and new clients to improve quality of health care as well as financial performance. They are involved in researching, designing, implementing and validating cutting-edge algorithms to analyze diverse sources of data and achieve targeted outcomes.
Genetic testing, a wave of the future, is also represented in Tennessee and employ data scientists. NextGxDx, a genetic testing company in Franklin, uses data scientists to develop new data products involved in genomic and genetic testing. These professionals work closely with marketing, sales, information technology and others in implementing, deploying and analyzing the company’s data assets. Their work is designed to make the testing process run much more efficiently and effectively.
Preparing for a Master’s Degree in Data Science in Tennessee
The optimal time to begin planning for a master’s degree in data science is during undergraduate school. This way, students can prepare to meet the admissions requirements imposed by graduate data science programs, which include:
- Completion of undergraduate and pre-master’s level coursework in mathematics, computers and science
- Obtaining work experiences in areas that showcase quantitative, database administration, computer programming or hacking skills
- Preparing for the GMAT or GRE, with particular emphasis on the tests’ quantitative sections
- Bridging any knowledge gaps through MOOCs or bridge courses, as required
Undergraduate Degree and Master’s Prerequisite Courses
Prerequisites for graduate data science degree programs typically include:
- A bachelor’s degree in data science, computers, mathematics or a related field, with a GPA of at least 3.0 on a 4.0 scale
- Undergraduate courses listed on a transcript including programming, statistics and probability, calculus I and II, and others that require quantitative skills
Related Work and Personal Experience
In addition to academics, applicants to graduate data science degree programs must have:
- At least five years of work experience involving quantitative skills
- Some type of personal experience involving quantitative skills, such as computer hacking, mathematics, coding, statistics, or data mining
- Letters recommending the applicant from professors or professionals who are familiar with the applicant’s qualifications
Tennessee work experiences that would meet these criteria include:
- Security Engineer- Ethical Hacking Knowledge Required at HCA in Nashville
- Programmer II at Health Trust in Brentwood
- Coder Analyst Specialist at Covenant Health Corporate in Knoxville
- Database Administrator at Experian in Franklin
Passing the GRE and GMAT Examinations
Passing graduate examinations, particularly the quantitative sections, is of great importance when applying to graduate data science degree programs. Admissions officers are typically looking for scores in the 85th percentile or above on the quantitative sections of the GRE or GMAT examinations.
GRE- the Graduate Record Exam (GRE) revised general exam’s quantitative reasoning section assesses a test-taker’s quantitative knowledge by posing:
- Algebraic questions on topics like algebraic expressions, graphing, linear and quadratic equations
- Arithmetic questions, on topics such as integers, roots and exponents, and factorization
- Geometric questions, on subjects including polygons, triangles, circles and quadrilaterals,
- Data analysis, including tables, graphs, probabilities, statistics, and standard deviation
Students may prepare for the GRE by studying:
- The Educational Testing Service (ETS)’s Math Review
- The Princeton Review’s GRE Practice Exams
- Kaplan Test Prep’s GRE Practice Exams
Subject area tests that help applicants to graduate data science degree programs are:
- Mathematics (Mathematics Test Practice Book):
- Discrete mathematics
- Introductory real analysis
- Probability, statistics and numerical analysis
- Physics (Physics Test Practice Book):
- Atomic physics
- Classical mechanics
- Lab methods and specialized topics
- Optics and waves
- Quantum mechanics
- Special relativity
- Statistical mechanics
The GMAT – The Graduate Management Admission Test includes a quantitative section that assesses an applicant’s knowledge of problem solving and data analysis by having them complete 37 questions in 75 minutes. Study aids for the GMAT may be found through:
Filling Gaps in Functional Knowledge By Means Of Bridge Courses or MOOCs
Bridge Courses – Some graduate data science degree programs will give applicants the opportunity to take bridge courses, if necessary. These courses, which are at the pre-master’s degree level, are designed to compensate for functional knowledge gaps an applicant may have. Many colleges and universities offer these courses online or in-person. Graduate data science degree programs usually offer bridge courses in subject areas such as:
- Computer programming languages, particularly C++, Java, Python, R and SAS
- Mathematics, particularly in topics like linear algebra, statistical methods and analysis of algorithms
Massive Open Online Courses (MOOCs)—These online courses provide another way applicants can fill in functional knowledge gaps, if they exist. They may be offered by online free or for a fee, and are given either by private invitation or via a public forum. MOOCs that may be of particular use to data science students include:
- Data mining
- Data analytics
- Machine learning
Earning a Master’s Degree in Data Science in Tennessee
While there are no traditional graduate data science degree programs in Tennessee, students there do have online graduate programs available to them. Related degrees that are available in Tennessee and online include:
- Master of Science in Data Science
- Master of Science in Predictive Analytics
- Master of Science in Data Management and Analysis
- Master of Science in Professional Science with a concentration in Informatics
These programs vary in length:
- Traditional master’s in data science degree programs run from 30 to 40 credits in length and are finished in 12 to 36 months, on a full- or part-time basis
- Online master’s in data science degree programs consist of about the same amount of credits, but give students more flexibility to take courses from anywhere, anytime. Often, they are completed more quickly than traditional graduate degree programs:
- 12 to 18 months for full-time students
- 24 to 36 months for part-time students Part-time students may earn a master’s degree in data science in two to three years
- 12 months for students of online accelerated programs
A graduate certificate in data science is another option for students. These programs range from 12 to 18 credits in length, and are completed in 12 to 18 months. Many employers, however, will not accept a graduate certificate when faced with another applicant with a master’s degree, so the graduate certificate is not as marketable or practical as a master’s degree.
Core Courses, Internship and Immersion Experience
Core coursework found in a typical master of science in science program includes:
- Experimental statistics I and II
- Introduction to data science
- File organization
- Database management
- Network and data security
- Data visualization
- Data mining
- Statistical sampling
A graduate internship may also be required. The student will be placed into a real-life data science work experience, and have the chance to interact and network with other workers and potential employers. Professors and employers grade the student’s performance during the graduate internship
Schools commonly require an immersion experience in a graduate data science program. This program consists of group case study work on a given topic. Students and faculty will meet in person and collaborate, providing more relationship-building and networking opportunities.
Key Competencies and Program Objectives
Competencies that employers expect graduates of master’s in data science programs to display are:
- Statistical analysis
- Data mining
- Machine learning
- Database management
- Network security
- Visualization of data
- Effective communication
Career Opportunities for Data Scientists in Tennessee with Advanced Degrees
Researchers in Tennessee have already recognized the importance of data science to a variety of industries and businesses in the state. In 2015, the Tennessee State College of Engineering held its first annual Workshop on Data Sciences, inviting mathematics, science and engineering professionals and researchers. The theme of this workshop was high-dimensional data analysis, with an emphasis on subspace clustering. It is likely to be just the first of many gatherings of professional data scientists and enthusiasts in the state of Tennessee.
(The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment. These examples were taken from a survey of job vacancy announcements for data scientists in Tennessee, completed in March 2016.)
Data Scientist at Digital Reasoning in Franklin
The headquarters of this computing company, which is just over 15 years old and works with intelligence agencies and financial institutions across the country, hires Data Scientists to work with its customers, some of whom require a top-secret clearance. Through predictive modeling, machine learning and data analysis, data scientists will offer Digital Reasoning’s customers business insights. In addition, they will work with the customer to educate them on business intelligence and training their own staff.
Applicants must have a graduate degree in a technical or analytic field, along with excellent written and verbal communication skills.
Data Scientist at Tescra, Inc. in Nashville
Tescra, one of the 5000 fastest-growing companies in the United States per Inc. magazine, is a systems integration provider. It was seeking a Data Scientist who would work with the company’s internal stakeholders to offer analytical solutions, models, prototypes and algorithms. The data scientist would also develop and deliver persuasive presentations and business cases to executives and clients.
Requirements for this position include an advanced degree in data science or a related field, along with five to ten years of work experience in the field.
Clinical Data Scientist at HealthTrust in Brentwood
This position is responsible for leadership and support in the development and implementation of HealthTrust purchasing group’s integrated clinical data system. Using visualization, programming and mathematics, the data science works in partnership with customer businesses to discover opportunities and insights.
In addition to a graduate degree in a related area, this position required three years of relevant work experience and experience in clinical or research writing.
Big Data Software Engineer at KPMG in Knoxville
This position with one of the world’s leading auditing companies is responsible for designing and implementing systems to handle big data and data science needs for Fortune 1000 companies who are KPMG’s clients. Using big data methodologies like Hadoop and SAP HANA, the big data software engineer translates business analytics problems into technical approaches in areas including market research, product development, risk management and public policy.
A graduate degree in a related field with two years of work experience is required for this position. Proficiency in Unix/Linux environments is also required.