The massive demand for data scientists across a variety of industries is only expected to grow in the coming years. According to communication juggernaut CenturyLink, 89% of business leaders believe big data will “revolutionize” business in a similar manner to the Internet, and the big data market is expected to top $84 billion in 2026.
Maine is no exception to the data science revolution. With organizations in the state’s public and private sectors alike relying on big data to develop cutting-edge strategies and solutions, data science is a critical part of that group.
Maine universities and employers haven’t been slow to team up to build up the state’s workforce for such important positions. In July of 2020, the Roux Institute at Northeastern University partnered with Sun Life in their Portland hub for innovative research and graduate education in technology and data science.
As one of the largest group benefits providers in the country, Sun Life is a big player in the insurance industry, and insurance is all about data. The very field of data science grew in part out of the actuarial calculations pioneered by insurers, and the industry has been one of the most voracious consumers of trained data scientists in recent years. With a $100 million grant to get the institute started and 11 corporate partners on deck so far, the Roux Institute is poised to help Maine industries out with more professional, graduate-educated data scientists for hire in the coming years.
Preparing for a Master’s Degree in Data Science in Maine
Professionals with a master’s degree in data science are highly sought after by Fortune 500 companies and innovative start-ups alike. As a result, admission to master’s programs in data science is highly competitive, with schools analyzing applicants’ educational and professional experience.
Undergraduate Degree and Master’s Prerequisite Courses
Master’s in data science programs typically look for students who meet an undergraduate profile that includes:
- A course load covering topics such as statistics, linear algebra, programming languages, calculus I and II, and quantitative methods
- A minimum GPA of 3.0
- A bachelor’s degree in a relevant quantitative field such as statistics, engineering, applied math, or computer science
In addition to these admission standards, programs consider applicant criteria in the following areas:
- GRE and/or GMAT exams
- Prior work experience
- Fundamental concepts
Preparing for Success on the GRE/GMAT Exams
To earn top consideration for admission, applicants typically have to score in the 85th percentile of the quantitative section of the GRE or GMAT. Applicants can also stack the odds in their favor with strong scores on the Verbal and Writing section of these exams.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:
- Algebraic topics such as algebraic expressions, functions, linear equations, and quadratic equations
- Arithmetic topics such as factoring, integers, exponents, and roots
- Data analysis, including topics such as statistics, graphs, standard deviation, probabilities, permutations, Venn diagrams, tables, and interquartile range.
- Geometry topics including the properties of triangles, quadrilaterals, polygons, circles, and the Pythagorean theorem
Students may prepare for the GRE by downloading a free program through Educational Testing Service (ETS) or signing up with the Princeton Review to take practice tests.
GMAT – The Graduate Management Admissions Test quantitative section consists of 37 questions designed to evaluate students’ data analytics skills, particularly in data efficiency and problem solving. Students may take practice exams through Veritas Prep and the Princeton Review to prepare for test day.
Relevant Personal and Work Experience for Admissions
Master’s in data science programs strongly consider applicants’ professional backgrounds, seeking students who have demonstrated strong communication skills and elite quantitative and analytical reasoning abilities. In particular, programs may consider the following when reviewing applications:
- Database administration proficiency
- Communication skills
- Total relevant work experience (five years is preferred)
- Programming proficiency in languages such as Java, C++, and Python
Just a few potentially qualifying work experiences in Maine could include:
- Data analysis at LL Bean
- Data management at Hannaford Brothers Company
- Cyber security at Maine Medical Center
Data Science Bootcamps as a Path to a Master’s Program or Straight Into the Job Market
Although a master’s program can unlock the very highest levels of the data science job market for you, just getting into a graduate program can be a real challenge. Programs are limited and demand is high. Only the very top candidates are accepted, and that usually means people with either some current expertise or experience with data science and analytic principles.
How do you get those kind of qualifications without having a master’s in the first place? Well, one route runs through a data science bootcamp, either in-person or online.
Bootcamps also give you an education in data science, but with a very different approach than a traditional degree. Conducted over only a few weeks or a few months, bootcamps skip much of the underlying academic theory and big-picture perspectives in favor of an intensely practical, hands-on education that drills down into the actual tools and techniques in-demand in the industry right now.
Usually delivered in a cohort style with a series of team-based projects that revolve around realistic development using genuine real-world datasets, bootcamps are offered at a range of skill levels and with different objectives. Some of the most advanced camps are aimed exclusively at current master’s and PhD holders, but entry-level bootcamps deliver the sort of training you’ll be looking for at the pre-master’s level.
While private organizations kicked-off the boot camp trend, many colleges are now getting into the game as well, bringing in their educational resources and experienced instructors. Several of these programs are available online in Maine today, including:
- Columbia Engineering Data Analytics Boot Camp
- Georgia Tech Data Science and Analytics Boot Camp
- Penn Data Analysis and Visualization Boot Camp
In addition to having a more academic university backing, these are unusual in that they are offered on a part-time basis. That’s a big advantage for anyone currently in school or trying to study while holding down a regular job.
Like other camps, though, they offer a ground-level introduction to data science essentials, including:
- Introduction to statistical and analytic libraries like Numpy
- Machine learning training
- Hadoop and Big Data processing
- SQL and database structures
They also include another service that is common of university programs: career development and placement services. That can range from resume polishing to interview prep to actually lining up possible job opportunities. Whether you take advantage of the job services or not, you’ll find yourself much better prepared for a master’s program at the end of the camp if getting a graduate degree is what you’re shooting for.
Bridge Courses and Massive Open Online Course (MOOC) Options for Applicants that Need to Fill Gaps in Knowledge
Even with strong professional backgrounds, some students lack one or more of the qualifications necessary to begin graduate data science coursework. To fill these gaps in knowledge, students have a couple of options besides a boot camp: bridge programs or massive open online courses (MOOCs).
Bridge Programs – Graduate schools will often provide bridge courses in fundamentals and programming for data science students who still have one or more gaps in knowledge. These are basically the same undergraduate courses that you might have taken while earning your bachelor’s degree in relevant fields, sometimes delivered in the summer so you can get up to speed just before your master’s program starts. They are offered to students who have already been accepted, but who need, in the view of the admissions committee, a little brush up before starting. Fundamental topics in these courses include:
- Analysis of algorithms
- Data structures
- Linear algebra
Programming courses allow students to become proficient in the languages necessary to begin graduate studies, such as:
MOOCs – Massive Open Online Courses – Many students elect to fill gaps in knowledge independently by enrolling in MOOCs. Delivered via video lectures, problem sets, and interactive forums, MOOCs are offered in an array of topics, giving students the opportunity to develop the diverse skill sets necessary to get into a master’s program. Because you take these before applying to your master’s program, you can bolster your odds of acceptance, as well as having more control over the subject matter studied and the timing and format of courses than you would have in a bridge program.
Earning a Master’s Degree in Data Science in Maine
Master’s programs in data science consist of curricular coursework and an immersion experience in the final semester. With both part-time and full-time learning formats available, students typically earn their degree in 18-30 months. Through accelerated learning formats, students can earn their degree in as little as 12 months. Typical graduate program titles include:
- Data Science Certificate
- Online Certificate in Data Science
- Graduate Certificate in Data Science
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MIDS)
- Master of Science (MS) in Data Science
- Data Mining and Applications Graduate Certificate
Aspiring data scientists in the state may choose to pursue their degree online through several accredited programs. Consisting of both live classes and self-paced coursework, online master’s programs in data science allow students to continue their careers while furthering their education.
Core Curriculum and Immersion
Master’s in data science programs provide students with the comprehensive knowledge necessary to draw actionable insights from massive amounts of data. Typical courses found in these programs include:
- Data mining
- Ethics and law for data science
- File organization and database management
- Data storage and retrieval
- Applied regression and time series analysis
- Statistical sampling
- Network and data security
- Machine learning and artificial intelligence
- Data research design and applications
- Information visualization
Students are able to apply the concepts learned in the classroom through the immersion experience – a collaborative project that simulates real-world problems that can only be solved with big data. Through this experience, students can demonstrate their talents and teamwork skills while networking with classmates, professors, and visiting prospective employers.
Key Competencies and Objectives
Master’s programs in data science equip students with the necessary tools to find success in the professional realm. Upon graduation, students are typically proficient in the following core competencies:
- Sophisticated data analysis
- Innovative design and research methods
- Working within a team setting
- Proficiency in programing languages like R and Python
- Association mining and cluster analysis
- Data survey analysis
Career Opportunities in Maine for Data Scientists with Advanced Degrees
The DICE 2020 Tech Job Report found that data engineer and senior data scientist were the two fastest growing tech occupations in the country, with between 32 percent and 50 percent year-over-year increases. That made them two of the three fastest growing technology jobs in the country, and those positions pop up in Maine just as they do elsewhere in the nation.
Data scientists in Maine may find career opportunities with exciting startups and established companies alike. Some of the state’s largest companies include:
- Hannaford Brothers Company, who employ between 8,500 to 9,000 Maine professionals
- Bath Iron Works Corporation, who employ between 5,501 to 6,000 Maine professionals
- L. Bean, who employ between 4,000 to 4,500 Maine professionals
- TD Bank North America, who employ between 3,000 to 3,500 Maine professionals
- Unum, who employ between 2,501 to 3,000 Maine professionals
The following job listings for data scientists in Maine are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment.
Lead Data Scientist & Architect, FT Days at Remedy Intelligent Staffing in New Gloucester – The role consists of acts including, but not limited to:
- Developing solutions that mine complex data and turn it into actionable information
- Assisting with the Data Architecture model to support Business Intelligence insights
- Acquiring, cleaning and structuring data from SQL and non-SQL databases, Hadoop, and structured and unstructured files.
Senior Data Scientist at CyberCoders (Remote) – The role would consist of duties including, but not limited to:
- Defining and developing algorithms
- Collaborating with the company’s production team and contributing to defining the logic of the production based on data stream integrity
- Performing advanced and specialized data analyses