Online Master's in Data Science for Jobs in Vermont

Due to the massive growth of technology over the last decade, data scientists in Vermont have become critical components to success in every business sector within the state. In fact, in 2011, the McKinsey Global Institute published a report stating that big data has “swept into every industry and business function.” In Vermont, data scientists have the opportunity to seek employment within many arenas, including some of the state’s largest home-based companies.

For example, National Life Group, a Vermont-based life insurance company, hires data professionals to manage and analyze large numerical datasets which store company and client information. At National Life Group, data scientists have the opportunity to work in the insurance industry while gaining experience working with large datasets, ensuring quality data mining, and performing data analysis with a team of data scientists. Another large Vermont based company, Green Mountain Coffee Co., also employs data scientists to work with company datasets, maintain databases, and create innovative solutions to downtrends in company sales.

Career opportunities have never looked better for data scientists with advanced degrees. According to a 2014 study cited by Diginomica, salaries of professionals in data science continue to trend upward. Professionals with master’s degrees set themselves apart from the crowd by ensuring their qualification in vital data science skills and their ability to succeed in the field. Data scientists in Vermont who earn their master’s degrees may pursue employment within insurance, finance and banking; retail, HR, and manufacturing; local government; the nonprofit sector, and beyond.

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

Universities seek out well-rounded, bachelor’s-prepared professionals to enroll in data science master’s programs. Admissions departments set highly selective admissions requirements, expecting candidates to display qualifications such as a high GPA in undergraduate coursework, scores in the 85th percentile or higher on either the GRE or the GMAT exam, and previous employment in the data science field.

Undergraduate Degree and Master’s Prerequisite Courses

In order to be considered for admission, candidates must meet several minimum requirements. Candidates are expected to hold a bachelor’s degree in a data science related field (statistics, computer science, engineering, or applied math), and to have a 3.0 or higher GPA during undergraduate studies.

Prerequisite courses are the building blocks for more advanced data science concepts. Admissions departments expect applicants to complete the following prerequisite courses during their undergraduate study:

  • Statistics
  • Calculus I & II
  • Linear algebra
  • Programming

Along with completion of prerequisite courses, applicants must score in the 85th percentile on either the GRE or the GMAT exam and have 5-7 years of prior work experience in the data science field.

In order to succeed in a data science master’s program, candidates are expected to be familiar with data structures, algorithms, analysis of algorithms, and linear algebra. Universities prefer that candidates have prior work experience in these areas.

Entrance Exam Scores

In order to meet admissions requirements, students may choose to take either the Graduate Record Exam (GRE) or the General Management Admission Test (GMAT). Both exams offer a similar quantitative section which is critical to the data science master’s student. The verbal and writing sections on each test are also important scores for potential master’s students. Applicants are required to score in the top fifteen percent in the quantitative section on either exam in order to be considered for entrance to data science master’s programs.

GRE Exam

The quantitative section of the GRE is the most critical component for master’s programs candidates. The GRE exam’s quantitative section will evaluate the student’s knowledge of the following topics:

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

Students may prepare for the GRE by visiting the official GRE website, which offers preparation guides, sample questions, and free practice exams.


The General Management Admissions Test (GMAT) also evaluates student’s quantitative skills and familiarity with data analysis. The quantitative section consists of 37 questions involving the following topics:

  • Data analysis
  • Problem solving
  • Data efficiency

Students may prepare for the exam by taking GMAT practice exams, available through The Princeton Review and Veritas Prep.

Prior Work Experience

Most master’s programs seek professionals with 5-7 years of experience in a data science field. In addition to work experience, admissions departments value a diverse skill set, including strong communication skills, programming proficiency in languages such as JAVA, C++, and Python, coding and hacking skills, data mining, and database administration.

In Vermont, bachelor’s prepared data scientists may gain the required 5-7 years of experience through several different avenues. The following examples are types of data science positions that will build the required experience:

Data Coordinator at Keurig Enterprise in Waterbury, Vermont, maintaining company workflow by building and maintaining databases and overseeing database infrastructure. The position uses data integration to coordinate several different company systems.

Data Analyst at Dealertrack in Burlington, Vermont, gathering, analyzing, and monitoring data, tracking company processes, providing data quality assurance, and assisting with team documentation of processes.

Data scientist at local nonprofits, small start-ups, or government offices, gaining experience managing data sets, working on a team of data scientists, analyzing data, and writing script.

Online Data Science Bootcamps to Get You Job-Ready or to Prepare for a Master’s Program

Start or advance your career in the booming field of data analysis. This 24-week boot camp teaches the fundamentals of Programming in Excel, Fundamental Statistics, Python, SQL, HTML/CSS, Tableau, and more. Click for more info:

Columbia Engineering Data Analytics Boot Camp
Georgia Tech Data Science and Analytics Boot Camp
Penn Data Analysis and Visualization Boot Camp

Bridge Programs and Massive Open Online Course (MOOC) Options for Master’s Programs Applicants Who Do Not Meet Admission Criteria

Data science master’s programs require applicants to possess excellent educational history, work experience, and a diverse skill set which will allow them to succeed in the program. Prerequisite courses such as statistics and programming languages are building blocks to more advanced concepts. Because of the diverse requirements for admission, most master’s programs offer bridge courses for candidates who might be missing one of the required courses or fundamental concepts.

Bridge programs are offered in two areas:

  • Fundamental bridge programs, including courses in linear algebra, algorithms and analysis of algorithms, and data structures
  • Programming bridge programs, including essential programming languages such as Python, JAVA, and C++

Candidates may also choose to supplement their education outside of the master’s program by enrolling in MOOCs, online education programs consisting of problem modules, lectures, and the opportunity to network with data science professors. There are many excellent MOOC hosts available for students. A list of 99 top-ranked MOOC programs is available for students’ perusal.

Earning a Master’s Degree in Data Science in Vermont

Currently, there are a handful of master’s programs in data science within the state of Vermont; however, many fully-accredited online programs are also available nationwide. More and more working professionals prefer the flexibility of an online program. Online programs are widely respected by employers, and are offered in full-time, part-time, and accelerated options. Full-time options can be completed in 18 months, part-time programs can be completed in 32 months, and accelerated options can be completed in as little as 12 months.

Most programs include an immersion experience in the last semester that will require the student to visit campus. The immersion experience is an intensive group project that gives students the opportunity to network with professors and peers.

Students may choose from several degree programs:

  • Master of Science (MS) in Data Science
  • Graduate Certificate in Data Science
  • Data Mining and Applications Graduate Certificate
  • Master of Information and Data Science (MIDS)
  • Master of Science in Data Science (MSDS)

Curriculum Content and Core Coursework

Coursework within Master’s programs will vary, but core courses will focus on essential skills required for data science positions. All programs will consist of a combination of the following topics:

  • File organization and database management
  • Applied regression and time series analysis
  • Advanced managerial economics
  • Quantifying materials
  • Machine learning and artificial intelligence
  • Experiments and causal inference
  • Ethics and law for data science
  • Network and data security
  • Data visualization
  • Data storage and retrieval
  • Experimental statistics
  • Statistical sampling
  • Data research design and applications
  • Macro and micro scaling data
  • Data mining

Key Competencies and Objectives

Data science master’s programs will prepare students for the challenges of working in a diverse, technical field. Data science professions require a wide range of technical skills, including the ability to mine, collect, and analyze data, provide statistical sampling, understand database management and organization, and know how to cleanse data. In addition to understanding how to manipulate data, master’s program graduates will also have a thorough understanding of current programming languages critical to the field.

Along with the acquisition of technical skills, graduates of data science master’s programs will also have an awareness of how to build strong network security, and understand the ethics of working with sensitive or secure information, with a comprehensive knowledge of current and relevant laws regarding secure information.

Graduates of the program will possess a well-rounded skill set, knowledge of relevant concepts and laws, and excellent communication skills. They will easily able to communicate with team members and visualize relevant data insights into reports. Master’s-prepared students will enter the field with a diverse range of knowledge, increased marketability, and the opportunity to seek more advanced employment positions.

Career Opportunities for Data Scientists in Vermont with Advanced Degrees

In Vermont, data scientists are found working in industries that range from finance and banking, to healthcare and biotechnology, to manufacturing and logistics, 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 Vermont in March 2016.

Senior Data Scientist at Oracle in Montpelier, VT


  • Bachelor’s degree in data science/related field required, master’s degree preferred
  • 10 or more years of related experience


  • Design, develop and program big data systems
  • Generate actionable insights and solutions for clients
  • Interact with product teams to confirm data analysis
  • Integrate large datasets through development and coding

Data Scientist/Analyst with Illume Advising, Burlington VT


  • Bachelor’s degree in data science/related field required, master’s degree preferred


  • Data management, data cleaning, and statistical modeling
  • Interpreting results from data analysis
  • Running descriptive statistics and survey summaries of results

Data Analyst at Technical Connection, Inc. in Burlington, VT


  • Bachelor’s degree in data science/related field required, master’s degree preferred
  • Background in database administration or business analysis


  • Working with SharePoint, Visual Studio, and big data analysis

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