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 using data science to develop cutting-edge strategies and solutions.
Public Sector’s Use of Data Science
Maine’s Office of Information Technology has been shifting its focus from data analysis to innovative data science application. In fact, the Office recently posted a data science internship opportunity, seeking a candidate to help with the following:
- Building predictive models based on large sets of data
- Creating insights that help government leaders, business leaders, and citizens make data-driven decisions
- Using statistical, mathematical, and machine-learning techniques to assist in the research and development of data-visualization apps, predictive models, and decision-making tools
Private Sector’s Use of Data Science in Manufacturing and Agribusiness
Several reports published by international management consulting firm McKinsey & Company have indicated that data science will significantly influence manufacturing and agribusiness, two industries that feature prominently in Maine.
Maine organizations exported hundreds of millions of dollars worth of manufacturing products in FY 2014, including:
- Civilian Aircraft, Engines, and Parts, $98 million
- Electronic Integrated Circuits, $70 million
- Paper, $57 million
Manufacturing companies are employing data scientists to develop cost-saving strategies from the machine level to organization-wide practices.
Agriculture plays a large role in Maine’s economy, with the state exporting $349 million in lobster and $22 million in fresh blueberries and cranberries in FY 2014. Data science is rapidly influencing agricultural practices, with farmers using real-time data collected by unmanned aerial vehicles to make efficient, cost-effective decisions.
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 to master’s programs in data science, students would typically have to score in 85th percentile of the quantitative section of the GRE or GMAT. Students can also position themselves for admission 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, quadratic equations, and graphing
- 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)
- Data mining ability
- Programming proficiency in languages such as JAVA, C++, and Python
- Coding skills
- Hacking skills
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
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 would either enroll in 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. 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. Typically consisting of learning formats such as filmed 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 for admission to master’s programs.
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. Students who choose part-time and full-time learning formats can typically earn their degree in 18-30 months. Through accelerated learning formats, students can earn their degree in as little as 12 months. Completing these programs leads to credentials such as:
- 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
As of March 2016, there are no campus-based master’s programs in Maine specifically dedicated to data science. However, 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 may 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
- Experiments and causal inference
- Data research design and applications
- Information visualization
- Advanced managerial economics
- Visualization of data
- Scaling data – macro and micro
- Quantifying materials
- Experimental statistics
Students are able to apply the concepts and skill sets of curricular coursework through the immersion experience – a collaborative project that simulates real-world data application. 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 analyses
- Innovative design and research methods
- Work within a team setting
- Proficiency in programing languages such as GitHub, SAS, Python, and Shiny by Rstudio
- Association mining and cluster analysis
- Database queries
- Interpretation and communication of results
- Hash algorithms, cyphers, and secure communications protocols
- Data survey analysis
Career Opportunities in Maine for Data Scientists with Advanced Degrees
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 8,000 to 8,500 Maine professionals
- Bath Iron Works Corporation, who employ between 5,000 to 5,500 Maine professionals
- L. Bean, who employ between 4,500 to 5,000 Maine professionals
- TD Banknorth, who employ between 3,000 to 3,500 Maine professionals
- Unum, who employ between 3,000 to 3,500 Maine professionals
- Idexx Laboratories, who employ between 1,001 to 1,500 Maine professionals
The following job listings for data scientists in Maine, sampled in March 2016, 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