Online Master's in Data Science for Jobs in Virginia

Data scientists in Virginia with master’s degrees have the benefits of increased marketability, the opportunity to work within many different industries across the state, and substantial potential for salary increase. In fact, according to a study published by executive recruiting firm Burtch Works, the salaries of senior managers in data science increased by 8% in 2014. Data scientists in Virginia also have the advantage of being employed in one of the most well-paid regions for data scientists, the Northeast, according to the Burtch Works study.

In addition, Virginia offers data scientists many employment opportunities. Virginia is home to Apex Systems, the third largest IT staffing firm in the US. As a company which uses specialized technology to serve clients across all industries, data scientists at Apex have the unique ability to work with clients from many different industries. Apex data scientists must be well-rounded in software development, algorithms, and big data in order to provide creative solutions to their clients’ individual needs. Outside of the tech industry, data scientists in Virginia may seek employment through large companies such as Boeing, which relies on the expertise of data scientists to track company processes and build a network of cyber security, or jobs in smaller local start-ups building database architecture and algorithms to mine data. In addition, data scientists may choose to seek employment with the local government, healthcare, or a myriad of other options.

Earning a master’s degree in data science prepares professionals to become leaders in the growing field of technology. Master’s-prepared data scientists are highly sought after professionals with a diverse skill set and the ability to lead a team of data scientists. More and more employers are seeking out data science professionals with advanced degrees, making it an ideal time to seek master’s credentials.

Preparing for a Master’s Degree in Data Science in Virginia

Bachelor’s prepared candidates seeking a master’s in data science are required to meet a variety of highly selective qualifications. Candidates must have an excellent track record, including undergraduate studies, prior work experience, knowledge of prerequisite concepts, and high entrance exam scores.

Undergraduate Degree and Master’s Prerequisite Courses

Applicants to data science master’s programs are required to meet several minimum qualifications in order to be considered for acceptance. These requirements include:

  • Bachelor’s degree in a related field (statistics, computer science, engineering, or applied math)
  • Minimum of 3.0 GPA during undergraduate studies

Applicants must also complete required prerequisite courses before enrolling in the program. Required prerequisite courses include statistics, calculus I & II, linear algebra, and programming.

In order to be accepted into a master’s program, candidates must demonstrate knowledge of these fundamental concepts, score in the top 15 percent on either the GRE or GMAT exam, and have 5-7 years of prior work experience in a data science position.

Applicants must also possess strong familiarity with key concepts, including data structures, algorithms, analysis of algorithms, and linear algebra.

GRE/GMAT Scores

Applicants are required to score in the 85th percentile in the quantitative section of either the GRE or the GMAT exam to be considered for admission to the program. Strong verbal and writing scores are also considered vital for data science professionals.

The Graduate Record Exam (GRE)’s quantitative section will evaluate the following concepts:

  • Data analysis
  • Arithmetic
  • Algebra
  • Geometry
  • Statistics
  • Standard deviation
  • Tables, graphs, and probabilities

The official GRE website offers a wealth of preparation information, 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 a data science related field 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 and hacking skills, experience in data mining, and experience in database administration.

In Virginia, data science professionals can gain the required experience through many different entry-level positions. Examples of the type of employment that would satisfy admissions requirements include:

Junior data scientist & software engineer at Nobilis in Falls Church, VA, engineering solutions to issues within data systems, conducting research, and coding within applications.

Data scientist at Keywcorp in Springfield, VA, working with geographic information systems and performing data analysis and logical data processing.

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.

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, especially data mining and analysis and programming languages. Because of the diversity of skills required, most data science master’s programs offer bridge programs which allow students to fill the gaps in required topics.

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 hosts, students may choose highly ranked offerings through the Online Course Report’s list of the 50 most popular MOOCs.

Earning a Master’s Degree in Data Science in Virginia

Although there are a few data science master’s programs offered in the state of Virginia, many professionals prefer the flexibility of online data science programs. Online programs offer fully accredited curriculum and are widely respected by professionals and employers nationwide. 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
  • 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

Key Competencies and Objectives

Data science master’s programs seek to prepare students for the challenges of working in the field. Students are expected to become competent in the following areas:

  • Research design
  • Data mining
  • Machine learning
  • Statistical sampling
  • Data analysis
  • Communication and visualization
  • Ethics, privacy, and relevant law
  • Database management and file organization
  • Programming languages such as Python, GitHub, and SAS
  • Database queries
  • Network security
  • Data cleansing

Career Opportunities for Data Scientists in Virginia with Advanced Degrees

In Virginia, data science professional with master’s degrees may seek employment across many different sectors, from finance, insurance and banking, to local government offices, to retail and manufacturing, to the nonprofit sector, among others.

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 Virginia in March 2016.

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

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