Like many parts of the country, the supply of data science professionals in the Southeast isn’t able to keep up with the white-hot demand for big data analytics in every sector. That shortage has hit Georgia harder than many southern states, however. According to DICE, a job search and career consultation firm, Atlanta’s industrial base of consumer goods, healthcare, and transportation share a heavy reliance on logistics – and modern logistics are heavily dependent on data science.
The director of enterprise architecture for the Coca Cola Company, based in Atlanta, recently reported the company’s shift towards “forward-looking analytics,” a strategy that involves forecasting rolling 13-month windows based on historical data. As the company puts an increased emphasis on putting big data to work in developing business strategies across its worldwide market, data scientists will continue to be needed to pull insights from massive data assets, and focus the findings right back into improving supply chain efficiencies and marketing strategies.
UPS, also headquartered in Atlanta, was one of the first to the data science game. Years ago the company implemented a simple strategy to modify driver behavior by restricting left turns through intersections – even when it seemed counterintuitive to do so. The strategy reduced idle times caused by waiting to turn across oncoming traffic enough to save 10 million gallons of fuel over an eight-year period. UPS expects 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. The company is now rolling AI out into customer tools in a similar way, helping them decide how, where, and when deliveries should be made, and automating customer assistance for faster, more accurate responses.
All the credit goes to data scientists working in Georgia. The demand for big data analytics isn’t showing any sign of slowing down as virtually every business sees opportunities to bring the same kind of efficiencies to their operations.
Preparing for a Master’s Degree in Data Science in Georgia
With businesses seeing major benefits from the application of data science, Georgia’s biggest companies are competing for the top talent in the field – and more often than not, they hold master’s degrees. You might find a job in the industry without a master’s, but without the level of expertise and skill to develop the kind of innovative solutions that companies need, you can’t expect to lock down a top-tier position or the salary that comes with it.
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 a master’s program in data science, you will typically have to meet the following minimum qualifications:
- Possess a bachelor’s degree in a field such as statistics, computer science, engineering, or applied math
- Earn a 3.0 GPA or higher during undergraduate studies
- Complete prerequisite courses, which typically include the following:
- Calculus I & II
- Linear algebra
In addition to these minimum requirements, admissions offices consider your background knowledge or accomplishments in the following areas:
- Fundamental concepts of data science and statistics, including:
- Data structures
- Algorithms and analysis of algorithms
- Linear algebra
- GRE and/or GMAT exams
- Prior work experience
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 committees may also consider strong scores in the Verbal and Writing sections of these exams to evaluate applicants’ communication skills—brilliant data analysis isn’t worth much if you can’t communicate your findings to end users and consumers.
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. Programs typically consider the following when analyzing your professional experience:
- Communication skills
- Programming proficiency in languages such as Java, C++, and Python
- Coding 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
Choosing a Data Science Bootcamp in Atlanta or Online to Gear Up for a Master’s Degree or to Prepare for Your Career
One way to equip yourself with the knowledge and experience you need to be accepted into a master’s-level data science program, or to get into a job in the field, is to enroll in a data science bootcamp.
A bootcamp, as the name implies, is a rigorous, time-compressed, focused course in data science skills development. Bootcamps aim to deliver practical results rather than theoretical underpinnings, and may last from one to nine months. In the past they were offered primarily by private, for-profit companies, but today the format has become popular enough that even major universities are starting to roll them out.
One of those options is the Georgia Tech Data Science and Analytics Boot Camp, offered both on-campus in Atlanta, or online through a virtual classroom experience.
In 24 weeks of part-time, evening and weekend coursework, the camp puts you through an intensive, practical introduction to data science skills, including:
- Python programming
- Statistical modeling
- Advanced Big Data Analytics with Hadoop
- Machine Learning
Although you won’t earn college credits, you will get heavy exposure to real-world techniques and principles of qualitative and quantitative analysis, delivered by instructors with experience in the field. And you’ll do it working on live data sets, addressing the kinds of real-world problems that employers actually put their data scientists on.
Like most bootcamps, the Georgia Tech one offers career counseling and resume and interview prep services as part of the package, so you can use it to roll right into a career in the field if you prefer.
Different bootcamps are targeted at different levels of expertise and may have different entry requirements; for the Georgia Tech camp, being 18 and having a GED are all you need, although a bachelor’s and two years work experience are preferred. More advanced programs have higher requirements, but an entry-level camp like Georgia Tech’s is a good steppingstone toward a master’s in the field.
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. If a bootcamp isn’t your speed, you can also look at MOOCs as a way to fill gaps in knowledge prior to applying to a master’s program, or you may take advantage of bridge programs available through schools that offer master’s programs in data science.
Fundamental and Programming Bridge Courses – If you have met all enrollment criteria other than some basic proficiencies and that have been accepted to a master’s program in data science, you will probably be asked to 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… although many are now based on curriculum offered by big-name universities.
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
Data science students in Georgia have access to a number of prestigious on-campus degree programs, but like students anywhere in the country, you can also 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 often 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
The realm of data is a large one, and it comes in a mind-blowing variety of formats and degrees of quality. Moreover, it’s being put to a tremendously wide array of uses in fields from politics to medicine to retail. 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 2019, CNBC.com ranked Georgia as the 6th 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 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 $73.3 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 use 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:
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 like 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.