A growing number of U.S. companies across a variety of industries are competing for top talent in the field of data science, and increasingly showing preference to master’s-prepared job candidates. Businesses of all kinds have come to rely on data scientists to mine diverse data assets and develop algorithms for machine learning as a way to develop innovative, cost-saving solutions and strategies. Two domains that feature prominently in Hawaii are the transportation industry and the military sector:
- Transportation – According to the Intelligent Transportation Society of America, “big data has arrived in the transportation industry, and is already being leveraged for new insights.” The infiltration of data science into the transportation sector could lead to increased opportunities for data scientists in Hawaii, with the state’s commercial airlines and shipping companies alike employing professionals to develop solutions in areas ranging from fuel use to route planning.
- Military – In 2013, Reggie Brothers, then the deputy assistant secretary of defense for Research, said data scientists are the most in-demand job for the military. The reason for this demand is the massive influx of data the military is collecting from unmanned vehicles, such as the autonomous real-time ground ubiquitous surveillance imaging system (ARGUS-IS), which can stream up to a million terabytes of data on a daily basis. This inundation of data is also stemming from naval ships, with the Naval Science and Technology Future Force estimating that ships will be able to store more than 1,000 terabytes of data by 2020. With 15 military bases in Hawaii, the state will undoubtedly present opportunities for qualified data scientists in the coming years.
Preparing to Enroll in a Master’s Degree Program in Data Science in Hawaii
Admission to master’s programs in data science is highly selective, with schools analyzing applicants’ past education, relevant work experience, and competency in a variety of areas related to the field. In most cases, it is expected that incoming graduate students have already mastered certain proficiencies and gained relevant work experience.
Undergraduate Degree and Master’s Prerequisite Courses
Applicants to master’s degree programs in data science would typically be expected to meet the following minimum qualifications:
- Minimum GPA of 3.0
- Bachelor’s degree in a quantitative field like applied math, computer science, statistics, or engineering
- A course load that includes coverage of key disciplines such as statistics, calculus I & II, linear algebra, and programming
Master’s programs seek applicants with working knowledge of fundamental concepts in the following areas:
- Linear algebra
- Data structures
- Algorithms and analysis of algorithms
Preparing to Do Well on GRE/GMAT Exams
Typically, applicants who have scored in the top 15 percent of the quantitative section of the GRE or GMAT are given top consideration for admission to these programs. Admissions programs may also consider strong scores in the Verbal and Writing sections of these exams to evaluate applicants’ communication skills.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:
- Arithmetic topics including exponents, factorization, integers, and roots
- Geometry, including the properties of triangles, quadrilaterals, circles, polygons, and the Pythagorean theorem
- Algebraic topics such as functions, algebraic expressions, quadratic equations, linear equations, and graphing
- Data analysis, covering topics like graphs, statistics, standard deviation, permutations, Venn diagrams interquartile range, tables, and probabilities
To prepare for the GRE, students may download a free program through Educational Testing Service (ETS) that allows them to take two sample tests. Additionally, students may sign up with the Princeton Review to take a practice exam.
GMAT – The Graduate Management Admissions Test’s (GMAT) quantitative section consists of 37 questions designed to evaluate students’ data analytics skills, particularly in problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through the Princeton Review and Veritas Prep.
Relevant Work Experience
Applicants who have demonstrated exceptional quantitative and analytical reasoning abilities and strong communications skills through prior work experience are also given top consideration for admission to master’s in data science programs. Programs typically consider the following when analyzing an applicant’s work credentials:
- Total relevant work experience (five years is preferred)
- Communication skills
- Database administration proficiency
- Coding skills
- Programming proficiency in languages such as JAVA, C++, and Python
- Hacking skills
- Data mining ability
Potentially qualifying work experiences in Hawaii could include:
- Cyber security at a major Hawaiian bank such as Bank of Hawaii or Territorial Savings Bank
- Data analysis at Matson, Inc.
- Programming for Hale Koa Hotel
Bridge Courses and Massive Open Online Course (MOOC) Options for Applicants Who Need to Fill Gaps in Functional Knowledge
Aspiring data scientists may lack functional knowledge in one or more areas required to begin graduate-level coursework. To earn these remaining qualifications, individuals would complete bridge courses once they are accepted into a master’s program but prior to transitioning into formal graduate studies, or Massive Open Online Courses (MOOC) to fill gaps in knowledge prior to applying.
Bridge courses are for students that have already been accepted into a master’s program in data science and offered as a precursor to beginning graduate studies. These courses generally take about 15 weeks to complete and are offered in one of two fucus areas. Fundamental Bridge Programs are designed for students who need to complete coursework in linear algebra, algorithms and analysis of algorithms, and data structures. Programming Bridge Programs are designed for students who need to become proficient in one or more of the mandatory programming languages required for admission to a master’s degree program.
MOOCs allow aspiring data science graduate students to fill gaps in their knowledge online through filmed lectures, problem sets, and interaction with professors and teaching assistants prior to enrolling in a graduate program.
Earning a Master’s Degree in Data Science in Hawaii
Through master’s programs in data science, students are able to prepare for advanced careers in the field through a blend of coursework and immersion experiences. Students who complete these programs through part-time and full-time learning typically earn their degree in 18-30 months, while accelerated learning formats allow students to earn their degree in as little as 12 months. By completing these programs, students may earn degrees with titles that include:
- Graduate Certificate in Data Science
- Data Mining and Applications Graduate Certificate
- Master of Information and Data Science (MIDS)
- Online Certificate in Data Science
- Master of Science (MS) in Data Science
- Master of Science in Data Science (MSDS)
- Data Science Certificate
With no specific master’s degree programs in data science available at campus locations in Hawaii, the state’s aspiring data scientists take advantage of accredited online programs that allow them to earn such degrees as the Master of Science in Data Science (MSDS) or the Master of Information and Data Science (MIDS). These programs consist of both self-paced coursework and live classes, allowing students to further their education without sacrificing current work obligations.
Core Curriculum and Immersion
Coursework in master’s programs in data science is designed specifically to meet the data skill demands of the world’s most profitable and innovative companies. Just some of the courses often found in these programs include:
- Machine learning and artificial intelligence
- File organization and database management
- Advanced managerial economics
- Information visualization
- Applied regression and time series analysis
- Data research design and applications
- Visualization of data
- Ethics and law for data science
- Data storage and retrieval
- Data mining
- Statistical sampling
- Quantifying materials
- Network and data security
- Experimental statistics
- Scaling data – macro and micro
- Experiments and causal inference
In addition to didactic coursework, students would complete an immersion experience, which consists of collaborative work on a project designed to simulate real-world data application. These experiences provide students with the opportunity to establish working credentials and demonstrate their talent in a team-based setting.
Key Competencies and Objectives
Through master’s programs in data science, students should gain proficiencies that include, but are not limited to:
- Being able to work in teams to achieve specific goals
- Being able to conduct database queries
- Being able to run an analysis of survey data
- Being able to develop and conduct sophisticated data analyses
- Becoming familiar with hash algorithms, cyphers, and secure communications protocols
- Being able to interpret and communicate results
- Being able to conduct association mining and cluster analysis
- Learning programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
- Developing innovative design and research methods
Career Opportunities in Hawaii for Data Scientists with Advanced Degrees
The simultaneous growth of Hawaii’s transportation industry and the sector’s reliance on strategic data use is just one of several indicators that Hawaii will be a promising future location for aspiring data scientists. According to an annual investor report, Hawaiian Airlines carried more than 10 million guests in 2014, the most in company history. What’s more, Hawaii’s total recorded exports reached an all-time high of $1.5 billion in 2014, according to the U.S. Department of Commerce. As Hawaii’s geographic location forces the state’s economy to rely on air travel and international trade, this growth should only continue in the coming years, and bring with it increased employment opportunities in the field of data science.
The following job listings were taken from a survey of job vacancy announcements for data scientists in Hawaii completed in February 2016 (examples are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment):
Data Scientist at American Savings Bank in Honolulu – The data scientist would be expected to automate the predictive analytical models by leveraging data assets and utilizing statistical analysis. Additionally, the role would consist of forecasting outcomes to drive change in the company’s customer interactions and support data driven decisions.
Senior Manager Data Scientist, Machine Learning at Otsuka Pharmaceutical (Remote) – The role consists of tasks including, but not limited to, creating innovative methodologies for data, establishing strategic partnerships with technical leadership across functional areas, and building proof of concept systems.