Axiom Data Science, an informatics and software development firm headquartered in Anchorage, relies on a team of data analysts, data coordinators, data scientists, and data librarians who partner with local and international clients to develop databases according to the clients’ needs and previous research. Axiom has developed a database of non-native plant species in Alaska and created a mapping application showing trends in growth. The companies international work includes a sea network that tracks subsistence use harvests. As well as creating original databases, the company has also redesigned existing databases into mapping portals and catalogs, including data from shore stations, gliders, HF radar, moorings, and satellite images.
- Syracuse University - M.S. in Applied Data Science: GRE Waivers available
- SMU - Master of Science in Data Science - Bachelor's Degree Required.
- UC Berkeley - Master of Information and Data Science Online - Bachelor's Degree Required.
- Syracuse University - Master of Information Management Online
- Maryville University - Master of Science in Business Data Analytics
- Villanova Business - Master's in Analytics and Study Data Mining, Predictive Analytics Online
Data scientists in Alaska also have the opportunity to work with community-minded organizations like the Alaska Native Tribal Health Consortium (ANTHC), a non-profit organization providing health services, health education, and rural health improvement services to Alaskans, particularly the native people of Alaska. At ANTHC, data scientists manage a system that includes all of ANTHC’s projects, including services offered, prevention training, and rural health system construction. Data scientists with ANTHC are also responsible for gathering data related to the management of health services, inputting data into the system, maintaining the system and improving upon existing systems to develop a comprehensive resource for ANTHC.
Data scientists are found working in a diverse array of industries in Alaska, from banking, finance and insurance to retail, manufacturing and marketing; and from healthcare, biotechnology and the pharmaceutical industry to the nonprofit and public sectors. As the field of data science continues to grow, an increasing number of bachelor’s-prepared professionals are seeking advanced degrees in data science.
Preparing for a Master’s Degree in Data Science in Georgia
Master’s-prepared candidates in data science have the opportunity to market themselves in many different sectors. Because of the high skill level required for these positions, master’s programs are often highly selective and set high admission standards for both educational and work history.
Undergraduate Degree and Master’s Prerequisite Courses
Applicants to data science master’s programs must meet certain minimum requirements, which often include:
- Bachelor’s degree in a related field such as statistics, computer science, engineering, and applied math
- Minimum 3.0 GPA in undergraduate coursework
Prerequisite courses for data science students most often include the following:
- Linear algebra
- Programming languages, especially JAVA and Python
Along with prerequisite requirements, master’s programs also consider the applicant’s work experience, GRE/GMAT exam scores, and fluency with fundamental concepts.
Data science coursework builds upon an established set of skills. In order to enroll directly into a master’s program, students will need to have educational or work experience in the following areas:
- Data structures
- Algorithms and analysis of algorithms
- Linear algebra
In order to be considered for admission, master’s program applicants are required to score in the top 15 percent of the quantitative section of either the GRE or the GMAT exam. Universities place special emphasis on the verbal and writing sections of the exams, expecting applicants to be excellent communicators.
The GRE’s quantitative section will evaluate:
- Data analysis, including statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
- Arithmetic, including integers, factorization, exponents, and roots
- Algebraic topics, including algebraic expressions, functions, and linear equations
- Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem
The Graduate Management Admission Test (GMAT) also includes a quantitative section which will include questions on problem solving and data efficiency. Students may prepare with full-length practice exams hosted by The Princeton Review and Veritas Prep.
Prior Work Experience and Related Skills
Prior work experience in a data science field is essential for admission to most master’s programs. In additional to 5-7 years of employment experience in a data science related field, admissions offices consider an applicants proficiency in the following skills:
- Programming languages, especially JAVA, Python, and C++
- Data Mining
- Database Administration
In Alaska, applicants may gain the required work experience through entry level positions that may include:
- Entry Level Java Programmer at NDD Systems in Anchorage, AL
- Entry Level System Administrator at Diligent Consulting, Inc., at Elmendorf AFB, AK
- Data analyst or programmer in local government offices
- Data scientist at local nonprofits
Bridge Programs and Massive Open Online Course (MOOC) Options for Applicants Who Do Not Meet Admission Criteria
Data science master’s programs require enrolling students to have a diverse set of skills and experiences. Because bachelor’s prepared candidates may not possess experience in each of the required skills, most universities offer bridge programs to allow students entering the program to gain proficiency as needed in the fundamental disciplines of data science.
Most universities offer two types of bridge programs:
- Fundamental (including linear algebra, algorithms and analysis of algorithms, and data structures)
- Programming (including languages such as Python, JAVA, C++)
Massive open online courses are another option for data science master’s students who wish to fill gaps i knowledge. MOOCs offer online problem modules, lectures, and the opportunity to seek instruction from professors, teaching assistants, and other students. There are many resources for prospective data science graduate students to access supplementary education tools proactively before applying to a master’s program.
Earning a Master’s Degree in Data Science in Alaska
Currently, there are no traditional in-state, on-campus master’s programs in data science in the state of Alaska. However, many working professionals prefer the flexibility of online programs, designed to complement a professional schedule. Full-time, part-time, and accelerated programs are available online.
Most programs will require an immersion experience that will require the student to visit campus in order to take part in a hands-on group project. Full-time programs are typically 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.
Data scientist students may choose from several different program titles:
- Master of Science in Data Science
- Master of Information and Data Science
- Graduate Certificate in Data Science
- Data Mining Graduate Certificate
- Data Science Graduate Certificate
Curriculum and Core Coursework
Master’s programs in data science vary from program to program, but all programs will require courses in basic fundamentals of data science. Core coursework will most likely include a combination of the following topics:
- File organization and database management
- Applied regression and time series analysis
- Advanced managerial economics
- Quantifying materials
- Ethics and law for data science
- Network and data security
- Visualization of data
- Data storage and retrieval
- Experimental statistics
- Statistical sampling
- Machine learning and artificial intelligence
- Experiments and causal inference
- Data research design and applications
- Scaling data – macro and micro
- Data mining
- Information visualization
Key Competencies and Objectives
Data science programs are meant to prepare students for employment in the field. Programs will require students to become proficient in the following areas:
- Statistical sampling
- Data collection and analysis
- Research design
- Data mining and machine learning
- Communication and visualization
- Ethics, privacy, and relevant law
- Database management and file organization
- Data and network security
- Data cleansing
- Programming languages such as Python, GitHub, and SAS
- Database queries
Career Opportunities for Data Scientists in Alaska with Advanced Degrees
According to Alaska.net, technology sector employment in the state is experiencing massive growth as the state continues to attract a growing number of high-tech firms. The website also reported that Alaska has seen 20 years of job growth, making it an ideal place to find employment, especially in the data science industry.
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 Alaska in February 2016.
Data Architect at Alaska Native Tribal Health Consortium in Anchorage – Design and develop data warehouse systems to support data of ANTHC, maintain data systems, and work with staff to modify existing databases
Business Intelligence Analyst in Anchorage – Develop and maintain data driven financial reports. Gather and document reporting requirements. Design, develop, test and implement data driven reports.