Data scientists in Virginia with master’s degrees have the benefits of increased marketability, and some serious salary potential. In fact, according to a study published by executive recruiting firm Burtch Works in 2019, the salaries of senior managers in data science went right up to $250,000 annually at the highest levels… $155,000 more than entry-level scientists.
Geospark Analytics, a Herndon firm that is recognized for world-class applied artificial intelligence solutions, just won a major contract in 2020 for the Army’s NORTHCOM command global threat and risk assessment platform. Data scientists have been key in producing the company’s Hyperion cloud-based platform that analyzes risks as diverse as pandemics and terrorist threats.
Outside of the tech industry, data scientists work for major defense contractors like Boeing, which has a substantial presence here working on DOD projects out of Crystal City; and just as often with smaller local start-ups working on innovations in database architecture and machine learning algorithms. And naturally, the dozens of federal agencies with operations here are always major employers for data scientists so close to the seat of government in D.C.
The complexity that massive and diverse data sets present requires unprecedented levels of expertise to analyze. Earning a master’s degree turns analysts, statisticians and applied mathematicians of all stripes into full-fledged data scientists capable of doing just that.
Preparing for a Master’s Degree in Data Science in Virginia
Although a master’s degree in the field is highly desirable, with the expectations businesses have for what master’s-prepared data scientists should be capable of, it’s not an easy credential to get. Demand is high and competition is fierce for the slots available. Candidates are expected to have an impressive background, including the right kind of undergraduate courses, prior work experience, knowledge of prerequisite concepts, and high entrance exam scores on standardized tests.
Undergraduate Degree and Master’s Prerequisite Courses
Your preparation should start before you even enroll in an undergraduate program, because the kind of degree you pick can have a major impact on your master’s enrollment potential. You’ll usually need a bachelor’s in some sort of quantitative or STEM field like statistics, computer science, engineering, or applied math.
You’ll have to hold at least a 3.0 and have prerequisite courses in statistics, calculus I & II, linear algebra, and programming under your belt.
GRE/GMAT Scores
You’ll also need to score in the 85th percentile in the quantitative section of either the Graduate Record Exam (GRE) or the General Management Admissions Test (GMAT) exam to be considered for admission to most data science programs. Strong verbal and writing scores are also considered vital for data science professionals; it’s not enough to have the insight of the century from your data analysis, you also have to be able to communicate it clearly to people who can use it.
Both GRE and GMAT have quantitative elements that will evaluate your knowledge of concepts like data analysis, algebra, statistics, and geometry.
The official GRE website offers a wealth of information on how to prepare, including a free practice exam, a preparation guide on the quantitative section, and free instructional videos.
If candidates choose to take The General Management Admissions Test (GMAT) rather than the GRE, they must also score in the top 15 percent of the quantitative section. The GMAT’s quantitative section is 37 questions long and covers the following topics:
- Problem solving
- Data analysis
- Data efficiency
- Graphs and tables
The official GMAT website offers candidates preparation materials and two free practice exams. The Princeton Review and Veritas Prep also host GMAT practice exams for additional preparation.
Prior Work Experience
Most master’s programs require candidates to have between 5-7 years of prior work experience in quantitative field or STEM role before admittance into the program. Admissions departments look for candidates with strong communication skills, programming proficiency (especially in languages such as Python, JAVA, and C++), coding skills, and experience in database administration.
In Virginia, data science professionals often get the required experience in jobs like these:
- Junior data scientist & software engineer at Nobilis in Reston, VA, engineering solutions to issues within data systems, conducting research, and coding within applications.
- Data scientist at Northrop Grumman in Chantilly, VA, using statistical analysis on a team of data scientists to derive insights and using data application to serve client’s needs.
Attending a Data Science Boot Camp in Richmond or Online to Meet Master’s Program Requirements and Get the Skills You Need to Be Job-Ready
Another way to get some hands-on experience is to enlist in a data science boot camp. Enlist! Sorry, we meant enroll.
Boot camps are pretty intense, even if they’re not exactly the same up-at-0500, jog-to-the-top-of-a-mountain-and-get-yelled-at-in-the-rain experience you would have in the real military.
What they do offer is a focused, fast-paced, practical crash course in data science as it is practiced in the real world. You develop the skills you will use on the job by undergoing a series of directed studies and learn-by-doing projects that expose you to some of the most cutting-edge tools in the field, using real datasets and addressing actual problems that data science can solve.
Bridge Programs and Massive Open Online Course (MOOC) Options for Master’s Program Applicants Who Do Not Meet Admission Criteria
Master’s program candidates are required to possess a diverse skill set, and master’s level courses will build off of fundamental concepts that you will be expected to know when you show up for class. Because of the diversity of skills required, most data science master’s programs offer bridge courses that allow students to fill gaps in functional knowledge.
Bridge programs are offered in two different areas:
- Programming bridge programs in essential languages (Python, Java, and C++)
- Fundamental bridge programs (includes linear algebra, algorithms, analysis of algorithms, data structures)
In addition to bridge programs, data science students may choose to supplement their education outside of the master’s program. Massive Online Open Courses (MOOCs) are an excellent resource for students wishing to gain a better understanding of programming languages, data mining and analysis skills, and other fundamental concepts. Through online lectures, problem modules, and interaction with data science professors, students can hone their personal skill set. While MOOCs are widely available through many different providers, big-name schools like Harvard and Stanford now make some of their regular courses available through MOOCs for a whole lot less than it would cost for traditional course delivery.
Earning a Master’s Degree in Data Science in Virginia
Even with relatively few data science master’s programs offered in Virginia, you do have some of the best in the business in D.C., as well as online. Many professionals prefer the flexibility of online data science programs. Online programs offer a fully accredited curriculum and are just as respected by employers and fellow data scientists. Online programs often offer three different types of program tracks:
- Full time, 18 months
- Part-time, 32 months
- Accelerated, 12 months
Most data science programs require students to complete an immersion experience in their last semester. The immersion program is a hands-on group project that will require online students to visit campus.
Students may choose from several program titles:
- 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
Curriculum Content and Core Coursework
Coursework within master’s programs will vary, but all courses require certain fundamental skills required for data science professionals. Programs will include a combination of the following topics:
- File organization and database management
- Applied regression and time series analysis
- Advanced managerial economics
- Ethics and law for data science
- Network and data security
- Visualization of data
- Machine learning and artificial intelligence
Key Competencies and Objectives
Employers looking for master’s-prepared candidates rightfully expect a consistent set of skills and competencies in those individuals. By the time you graduate from your program, you’ll need to have achieved high-levels of skill in subjects ranging from research design, to communication and visualization, to database query design and optimization.
You’ll also be expected to master more ephemeral concepts, such as data munging and cleaning, ethical considerations, and data storage selection and optimization. It’s all a package deal, and you will have to demonstrate your ability to tie it all together to land the top jobs in the field.
Career Opportunities for Data Scientists in Virginia with Advanced Degrees
Data science is a big part of the way financial services, insurance and banking, local government offices, retail and manufacturing run these days.
These job listings are shown as illustrative examples of the kind of opportunities you’ll find in Virginia. They are not meant to represent job offers or provide any assurance of employment.
Lead Data Scientist at Oracle in Richmond, VA
Requirements:
- Master’s degree in data science or a related field
- 10 or more years of experience in data science
Responsibilities:
- Designing and developing software to implement data testing
- Designing data architecture for individual projects
- Ensuring quality review processes of databases
Principal Data Scientist at Snagajob in Glen Allen, VA
Requirements:
- Master’s degree in data science or a related field
- 3-5 years of experience with machine learning techniques
- Prior experience with big data and large datasets
Responsibilities:
- Develop algorithms, test code, and perform predictive modeling for clients
- Research data mining and machine learning techniques
Data Scientist at Markel in Richmond, VA
Requirements:
- Bachelor’s degree in data science/related field required, master’s degree preferred
- At least one year of prior experience with data science in an insurance field
Responsibilities:
- Using data analytics to perform predictive modeling for clients
- Using internal and external data to build prototypes
- Providing training to junior members of team