According to the Atlanta Business Chronicle, only 8% of data scientists in the U.S. live in the Southeast, making qualified talent in Georgia “hard to find” and “very expensive.” With 18 Fortune 500 companies and a number of innovative start ups in Georgia actively competing for skilled data scientists, the state looks to be among the most promising in the U.S. for those interested in pursuing graduate work in the field.
- 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
- Villanova Business - Master's in Analytics and Study Data Mining, Predictive Analytics Online
The Atlanta-based Coca Cola Company is just one organization in Georgia that has relied on data scientists to interpret and model massive data assets. Recently, the company has shifted towards “forward-looking analytics,” forecasting rolling 13-month windows through historical data, according to Mathew Chacko, Coca-Cola’s director of enterprise architecture. As the company puts an increased emphasis on putting big data to work in developing business strategies and building shared platforms across its worldwide market, data scientists will continue to be needed to tackle massive data assets in areas ranging from its supply chain to marketing tactics.
United Parcel Service (UPS), also headquartered in Atlanta, is another major company taking active steps to maximize revenue through data science. Jack Levis, UPS Senior Director of Process Management stated in October 2015 that the company’s focus in the coming years will be on prescriptive analytics, utilizing data such as fuel costs in different cities, traffic conditions and the number of stops made by company drivers to develop cost saving strategies. But data science is nothing new to the logistics juggernaut. As early as 2004, data scientists with UPS came up with a strategy to modify driver behavior by having them avoid left turns, even when this seemed counterintuitive. This outside-the-box strategy actually reduced idle times caused by waiting to turn across oncoming traffic enough to save 10 million gallons of fuel between 2004 and 2012. Through a new data software system called ORION, Levis said he expects UPS to be able to implement new strategies to modify driver behavior even further, which could save $300-$400 million per year on fuel costs alone.
Preparing for a Master’s Degree in Data Science in Georgia
With businesses seeing major benefits from the application of data science, Georgia’s largest companies are competing for master’s-prepared data scientists.
Master’s programs in data science set highly selective admissions standards, analyzing applicants’ past education, work history, and competency in a variety of areas related to the field.
Undergraduate Degree and Master’s Prerequisite Courses
To be considered for admission to master’s programs in data science, applicants would typically be expected to meet the following minimum qualifications:
- Applicants must possess a bachelor’s degree in a field such as statistics, computer science, engineering, or applied math
- Applicants must earn a 3.0 GPA or higher during undergraduate studies
- Applicants must complete prerequisite courses, which typically include the following:
- Calculus I & II
- Linear algebra
In addition to these minimum requirements, admissions offices consider applicant criteria in the following areas:
- Fundamental concepts
- GRE and/or GMAT exams
- Prior work experience
Applicants must have working knowledge of fundamental concepts in the following areas:
- Data structures
- Algorithms and analysis of algorithms
- Linear algebra
Preparing for Success on the GRE/GMAT Exams
Typically, applicants who have scored in the top 15 percent of the quantitative section of the GRE or GMAT are given top consideration for admission to these programs. Admissions programs may also consider strong scores in the Verbal and Writing sections of these exams to evaluate applicants’ communication skills.
GRE – The Graduate Record Exam (GRE) revised general test’s quantitative reasoning section evaluates the following:
- Data analysis, covering topics like statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
- Arithmetic topics including integers, factorization, exponents, and roots
- Algebraic topics such as algebraic expressions, functions, linear equations, quadratic equations, and graphing
- Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem
To prepare for the GRE, student may download a free program through Educational Testing Service (ETS) that allows them to take two sample tests. Additionally, students may sign up with the Princeton Review to take a practice exam.
GMAT – The Graduate Management Admissions Test’s (GMAT) quantitative section evaluates students’ skills in data analysis. The quantitative portion consists of 37 questions related to problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through the Princeton Review and Veritas Prep.
Prior Work Experience
Applicants who have demonstrated exceptional quantitative and analytical reasoning abilities and strong communications skills through prior work experience are also given top consideration for admission to master’s in data science programs. Programs typically consider the following when analyzing an applicant’s work credentials:
- Communication skills
- Programming proficiency in languages such as JAVA, C++, and Python
- Coding skills
- Hacking skills
- Data mining ability
- Database administration proficiency
Potentially qualifying work experiences in Georgia could include:
- Analyzing medical data at Northeast Georgia Health System & Medical Center
- Data analysis at Delta Airlines
- Cyber security at Aflac
- Programming for Atlanta startups
Bridge Courses and Massive Open Online Course (MOOC) Options for Applicants that Need to Fill Gaps in Knowledge
Even aspiring data scientists with impressive professional backgrounds may lack one or more of the admissions qualifications set forth by master’s degree programs. These individuals would either proactively pursue MOOCs as a way to fill gaps in knowledge prior to applying to a master’s program, or may take advantage of bridge programs available through schools that offer master’s programs in data science.
Fundamental and Programming Bridge Courses – Students that have met all enrollment criteria other than some basic proficiencies and that have been accepted to a master’s program in data science would enroll in bridge courses prior to taking graduate-level courses. Bridge courses typically last 15 weeks and are available to fill gaps in knowledge related to either fundamentals or programming. Fundamental bridge programs offer courses in linear algebra, algorithms and analysis of algorithms, and data structures, allowing students to earn their outstanding qualifications, while programming bridge courses allow students to become proficient in the mandatory programming languages required before beginning graduate-level coursework.
MOOCs (Massive Open Online Courses) – MOOCs give aspiring data science graduate students the opportunity to further their education and fill gaps in their knowledge before applying to a graduate program. MOOCs typically involve online problem sets, filmed lectures, and interaction with professors and teaching assistants. These courses are offered online totally independent of schools that offer master’s programs in data science.
Earning a Master’s Degree in Data Science in Georgia
Master’s programs in data science prepare students for advanced careers in the field through a blend of coursework and immersion experiences. Through accelerated learning formats, students may earn their degree in as little as 12 months, while part-time and full-time learning typically takes between 18-30 months to complete. Successful completion of these programs may lead to degrees such as:
- Master of Science (MS) in Data Science
- Master of Information and Data Science (MIDS)
- Master of Science in Data Science (MSDS)
- Graduate Certificate in Data Science
- Data Mining and Applications Graduate Certificate
- Online Certificate in Data Science
- Data Science Certificate
As of 2016, there are no master’s programs in Georgia offering a specific degree in data science.
With no specific master’s degree programs in data science available at campus locations in Georgia, data science graduate students in the state take advantage of accredited online programs that allow them to earn such degrees as the Master of Information and Data Science (MIDS) or the Master of Science in Data Science (MSDS). Consisting of live classes, self-paced coursework, and immersion experiences, these programs allow students to earn their degree without sacrificing current work obligations.
Curriculum, Core Coursework
Master’s programs in data science offer courses targeted specifically to meet the data skill demands of the world’s most profitable and innovative companies. Examples of courses often found in these programs include:
- File organization and database management
- Applied regression and time series analysis
- Advanced managerial economics
- Quantifying materials
- Ethics and law for data science
- Network and data security
- Visualization of data
- Data storage and retrieval
- Experimental statistics
- Statistical sampling
- Machine learning and artificial intelligence
- Experiments and causal inference
- Data research design and applications
- Scaling data – macro and micro
- Data mining
- Information visualization
In addition to traditional courses, students are required to complete an immersion experience – a collaborative project designed to simulate real-world data application. Through these experiences, students are given the chance to demonstrate their talent in a team-based setting and establish working credentials before graduation.
Key Competencies and Objectives
Master’s degree programs in data science prepare students for the diverse challenges of working in the field. Upon graduation, students should be proficient in areas including, but not limited to:
- Statistical sampling
- Data collection and analysis
- Research design
- Data mining and machine learning
- Communication and visualization
- Ethics, privacy, and relevant law
- Database management and file organization
- Data and network security
- Data cleansing
- Programming languages such as Python, Shiny by Rstudio, GitHub, and SAS
- Database queries
Career Opportunities for Data Scientists in Georgia With Advanced Degrees
In 2014, both CNBC.com and Site Selection Magazine ranked Georgia as the best U.S. state for doing business, meaning qualified data scientists have ample opportunities to establish high-paying careers in the state. Just some of Georgia’s top business sectors that rely on the talents of data experts:
- Global transportation and infrastructure – Hartsfield–Jackson Atlanta International Airport, the world’s most active airport in terms of passengers since 1998, relies on data scientists to tackle data in an effort to provide solutions to issues related to everything from customer luggage, marketing success rates, and more.
- Agriculture – According to the Georgia Farm Bureau, agriculture contributes roughly $72.5 billion annually to Georgia’s economy. Data scientists work with producers to find new solutions to maximizing yields and sales while minimizing waste, as well as the state’s agricultural exporters to find new strategies for even more cost-efficient transportation methods.
- Food and Restaurants – Atlanta-based franchises Chick-Fil-A and Arby’s utilize the talents of data scientists in areas like geographic expansion.
The following were taken from a survey of job vacancy announcements for data scientists in Georgia completed in February 2016 (examples are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment):
Data Scientist at CHASE Professionals in Atlanta – The position consists of creating effective behavioral and predictive models, working with high volume data sets, recommending new algorithms and tools to support the Data Analytics function, and more.
Data Scientist at Infosys in Atlanta – Within the Practice Lead role, the data scientist would implement and execute strategies to create business solutions at a sub-practice level in areas such as Accounts Receivable, Quote to Cash, and Data analytics.
Data/Cognitive Scientist at Deloitte Consulting Products and Solutions in Atlanta –The role consists of day-to-day modeling and algorithm development and optimization, performing cognitive R&D work, collaborating with software engineers to implement productive algorithms and models, developing products, and more.