Data science is completely reshaping many industries and even the public service sector, but Kristin McClure, Vermont’s new Chief Data Officer (CDO), sees something even more revolutionary happening. As she steps in to fill the role as only the second person ever to hold the office, she believes that the importance of data science is starting to pervade the public consciousness.
“We’re a lot more aware of our data and connected to it,” she asserts in a 2020 interview with GovTech, “and I think it’s the literacy of data that has grown rapidly over the years—and the ability to frame decisions in the manner of ‘All right, what’s the data to support that?’”
But it’s definitely not just public service that is being reshaped by big data. Every sector of private industry is changing the way they do business based on a new awareness of the power of data to reduce costs and add to the bottom line. At National Life Group, data scientists are pushing actuarial analysis to new highs, while at Green Mountain Coffee Co., they’re streamlining supply chains and identifying down-trends in company sales to create innovative solutions for heading them off.
Career opportunities have never looked better for data scientists with advanced degrees. According to DICE, a major online job search engine, data science and engineering positions were two out of the top three fastest growing jobs in the tech industry between 2019 and 2020, growing by as much as 50 percent in one year. Professionals with master’s degrees set themselves apart from the crowd with qualifications and skills vital to success in the field. Bottom line is that a master’s gives you first pick of the most lucrative positions available around the state.
Preparing for a Master’s Degree in Data Science in Vermont
Graduate schools look for well-rounded, bachelor’s-prepared applicants to accept into the data science master’s programs they offer. Admissions standards can be highly selective, with candidates expected to display qualifications that include a high undergraduate GPA, scores in the 85th percentile on entrance exams like the GRE or GMAT, and some previous employment in a quantitative 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 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 typically expect applicants to have completed the following prerequisite courses in their undergraduate program:
- Statistics
- Calculus I & II
- Linear algebra
- Programming
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.
Entrance Exam Scores
In order to meet admissions requirements, students who don’t qualify for a waiver may choose to take either the Graduate Record Exam (GRE) or the General Management Admission Test (GMAT). Both exams offer a similar quantitative section that helps assess how ready applicants are for graduate-level data science curriculum. With communication being a critical part of the job, the verbal and writing sections on each test are also given consideration.
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.
GMAT Exam – 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 some professional experience in a data science related 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, or database administration.
In Vermont, bachelor’s-prepared data scientists may pick up that required experience through several different avenues. Here’s a few examples:
- Data Coordinator at Keurig Green Mountain 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.
- Work at local nonprofits, small start-ups, or government offices, gaining experience managing data sets, working with a team of data scientists, analyzing data, and writing scripts.
Online Data Science Bootcamps to Get You Job-Ready or to Prepare for a Master’s Program
Unfortunately, if you didn’t plan far enough ahead, you can find yourself in a position where you badly want to get into a data science master’s program but have not managed to acquire either the experience or the academic background to be taken seriously by an admissions committee.
Rather than having to return all the way to Go and start over, however, you can take another path: enroll in a data science bootcamp.
Although this is shorter path, and a whole lot cheaper than earning another bachelor’s degree, it may not be easier during those days you’re in class. You will face a demanding course load of material that covers:
- SQL and various SQL data stores
- Social media and big data mining
- Hadoop and NoSQL
- HTML5/CSS for data visualizations
- Python and R programming
- Specialist libraries like D3.js and Leaflet.js
It’s all delivered via a series of team projects that focus on teaching the practical aspects of data science through real-world datasets and problems that are the same type you would be asked to solve in a full-time position. Your instructors are drawn from exactly that sort of role themselves, fresh from active positions and full of cutting-edge techniques to pass along.
Most bootcamps are offered by private companies and require on-site participation, but a new type of camp is emerging. Offered for entry-level students and run through big name universities with their own regular data science programs, these are available on a part-time basis and delivered online during evenings and weekends for maximum flexibility:
- Columbia Engineering Data Analytics Boot Camp
- Georgia Tech Data Science and Analytics Boot Camp
- Penn Data Analysis and Visualization Boot Camp
The big-school backing gives you big-time resources and access to professional academics and career services departments, all of which serve to give you a lot of options for fine tuning your application for a job, or a master’s program in data science.
Bridge Programs and Massive Open Online Course (MOOC) Options for Master’s Programs Applicants Who Do Not Meet Admission Criteria
If you missed out on a handful of academic courses but manage to qualify in the experience department, you have some other options for brushing up on your skills before entering a master’s program. Because of the diverse requirements for admission, most master’s programs offer bridge courses for recently accepted students 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. These courses are also often offered by top-name universities or by industry stalwarts like Microsoft or IBM. They give you additional flexibility in picking and choosing so you can select the specific subjects you need and take the courses on your own time.
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 online programs, which offer 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
- Machine learning and artificial intelligence
- Ethics and law for data science
- Network and data security
- Data visualization
- Data storage and retrieval
- Data research design and applications
- Data mining
Key Competencies and Objectives
Data science master’s programs prepare students for the challenges of working in a diverse, technical field. The profession requires a wide range of technical skills, including the ability to mine, collect, and analyze data, develop statistical sampling methods, and understand database management and organization. In addition to understanding how to manipulate data, master’s graduates will also have a thorough understanding of current programming languages critical to the field.
Along with the acquisition of technical skills, graduates also develop 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 programs possess a well-rounded skill set that is complemented by excellent communication skills. They will easily be able to communicate with team members and visualize relevant data insights into reports.
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.
One thing they all have in common are hefty paychecks. A master’s degree is your ticket into one of the most lucrative fields in technology today. According to Robert Half, an executive recruiting firm that specializes in IT staffing, data scientists in Burlington can expect starting salary offers of between $97,000 and $167,000 per year depending on their experience and education.
The following job listings are shown as examples of some of those positions, and are not meant to represent job offers or provide any assurance of employment.
Senior Data Scientist at Oracle in Montpelier, VT
Requirements:
- Bachelor’s degree in data science/related field required, master’s degree preferred
- 10 or more years of related experience
Responsibilities:
- 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 Analyst at Technical Connection, Inc. in Burlington, VT
Requirements:
- Bachelor’s degree in data science/related field required, master’s degree preferred
- Background in database administration or business analysis
Responsibilities:
- Working with SharePoint, Visual Studio, and big data analysis