The field of data science, once described as the platform for an emerging force of industry-changing professionals, has since burst into the foreground of every major economic contributor in the Nation. No longer is it a budding new frontier; it has fully developed into a technological catalyst, and companies are clamoring to add highly skilled data scientists to their teams.
- SMU - Master of Science in Data Science - Bachelor's Degree Required.
- Syracuse University - M.S. in Applied Data Science: GRE Waivers available
- UC Berkeley - Master of Information and Data Science Online - Bachelor's Degree Required.
- Syracuse University - Master of Information Management Online
Despite this rising popularity, there is a severe shortage of qualified data scientists capable of meeting the growing needs of employers. This void has contributed favorably to the high salaries enjoyed by data scientists, particularly those with Master’s degrees, or higher levels of education. And, there is promise of even greater wages to come as the scope of influence within the profession becomes more widespread. According to executive recruiting firm, Burtch Works, the salaries for data scientists have substantially increased since 2014 at nearly every level of experience. In fact, data scientists possessing graduate-level degrees found management positions with salaries spiking upwards of 8% in just one year.
Opportunities for data scientists in Utah are seemingly endless, as the world of technology is fast finding its home base in the Salt Lake Valley. Dubbed “The Silicon Slopes,” Utah’s data science industry is gaining momentum with the aim of becoming the next hub of technological advancement in the United States. While entry-level positions are available, those with graduate degrees in data science will find the most promising career outlooks in Utah.
Preparing for a Master’s Degree in Data Science in Utah
Candidates applying for admission to a Master’s Degree in Data Science program in Utah must meet a variety of requirements, which include passing proficiency examinations with high scores, completing program-specific undergraduate courses, and possessing considerable work experience, and/or correlating internships, in data science field. Applicants can expect a very competitive selection process.
Undergraduate Degree and Master’s Prerequisite Courses
Admissions officers for Master’s Degree in Data Science programs throughout Utah will require the completion of a Bachelor’s Degree in a related field, such as Applied Mathematics, Engineering, or Business Analytics. Additionally, a minimum GPA of 3.0 for undergraduate studies is often mandatory.
Relevant Personal and Work Experience
Previous work experience in data analysis or data management is always beneficial when being considered for admission to graduate-level data science studies. Many admissions officers require that a Curriculum Vitae (CV) be submitted along with the application. This is used to determine the professional, academic, and experiential merit of the prospective student.
In addition to work experience, applicants to the Master’s program should have an ability to gather and comprehend intricate data statistics while effectively communicating their conclusions to others in a clear and concise manner.
For students looking to gain a foundation in data science on the work front before beginning a Master’s program of study, Utah’s Silicon Slopes offer many entry-level positions and internships in related fields.
Such companies include:
- Research Analyst at the State of Utah Department of Health in Salt Lake City, UT
- Director of Data Science at Progressive Leasing in Draper, UT
- Data Scientist at Mountain America Credit Union in West Jordan, UT
- Technical Intern at Northrop Grumman in Ogden, UT
Preparing to Score Within the 85th Percentile on the GRE/GMAT
The importance of scoring above average on the Graduate Record Exam (GRE) and/or the Graduate Management Admissions Test (GMAT) cannot be understated in the admissions process. When preparing for these examinations, students must keep in mind that while many schools in Utah don’t have a minimum score requirement, candidates who receive scores in the 85th percentile will be given greater consideration.
Most admissions directors for data science graduate programs place the highest priority on the Quantitative Section of the GRE/GMAT. However, students should not disregard the importance of the exam as a whole. Significant scores in the Verbal and Writing Sections will be expected, as well. It is essential that the applicant demonstrates an extensive working knowledge of concepts within the data science field, and is capable of communicating that knowledge clearly.
The following is a sampling of the basic knowledge and correlating skills tested in the Quantitative Reasoning portion of the GRE:
- Basic arithmetics: integers, square roots, factorization, and exponents
- Algebraic expressions, linear and quadratic equations, graphing, and functions
- Geometrical equations, proofs, and the Pythagorean Theorem
- Specific data analysis topics including standard deviation, permutations, tables, probabilities, statistics, etc.
Practice exams and study guides are available on the official GRE website to aid in preparation.
The Graduate Management Admissions Test (GMAT) surveys the aforementioned subjects and includes more subjective word problems in an effort to measure the student’s capacity to analyze given data sets and organize the information into applicable conclusions based upon their findings.
Test prep resources and study guides for the GMAT can be accessed through the official website. Supplemental practice exams are offered through Veritas Prep and The Princeton Review.
The University of Utah offers prep courses through the Office of Continuing Education and recommends the following resources to supplement their classes:
- Khan Academy (Quantitative Section Only)
- GMAT Prep Now Youtube Channel
- Kaplan GMAT Youtube Channel
- Dominate the GMAT Youtube Channel
- DoD MWR Library (For Military Personnel)
The University of Utah offers this waiver: “Applicants with 5 or more years of senior-level leadership experience in IT or operations that includes managerial responsibility may request to have their work experience considered in lieu of a GRE/GMAT score.”
Gaps in Functional Knowledge Can Be Filled With MOOCs and Bridge Courses
If GRE/GMAT test scores are lower than desired, students can address topical weaknesses by supplementing education with Massive Open Online Courses (MOOCs) and Bridge Courses, which are available in both online and live-class options.
MOOCs help students grow in knowledge and skill in an independent study format. Once enrolled, students gain access to archived online classes, lectures, and study materials that serve to fill any gaps in prerequisite comprehension so that the student can begin Master’s-level study in data science. These courses provide introductory foundations within the student’s chosen emphasis, depending upon their needs.
Students can also take advantage of Bridge Courses, which are offered through individual graduate schools once they have been accepted into the Master’s program. These are beneficial for those who have met the initial admission requirements, but lack the area-specific courses needed to begin graduate-level studies in data science. For example, students who possess an undergraduate degree in an unrelated field can take Bridge Courses in the following subjects to augment their base knowledge:
- Python for Data Science
- Introduction to Linear Algebra
- Fundamentals of Data Structures and Algorithms
Bridge Courses are typically 15 weeks long. Once completed, students can move on to the official coursework within their graduate program.
Earning a Master’s Degree in Data Science
It is clear that the field of data science is one of the fastest growing career paths in Utah. As such, colleges and universities are actively working to create more programs of study, especially at the graduate level. New students are inundating data science graduate schools every year, vibrantly paving the way for highly competitive and densely populated programs.
In light of the growing demand, graduate schools are providing groundbreaking avenues of study, both online and in live classrooms.
Some programs of study available in the state of Utah include:
- The University of Utah, Salt Lake City, UT
Master of Science (M.S.) in Computing with an Emphasis in Data Management and Analysis
- The University of Utah, Salt Lake City, UT
Master of Science (M.S.) in Information Systems
- Utah State University, Logan, UT
Master of Science (M.S.) in Computer Science
- The University of Utah, Salt Lake City, UT
Master of Science (M.S.) in Computing/Big Data Certificate
A typical M.S. program of study requires between 30-36 credit hours, on average. 2/3 of those credits are generally made up of core courses. For traditional students taking classes full-time, the graduate coursework can be completed within 3 semesters. Some accelerated learning programs can be found which allow a fast-track curriculum to be completed in 12 months, or 2 semesters. Part-time programs are less common, however, some schools allow extended completion times that stretch coursework over 5 semesters. Online and night classes are often available for students with full-time jobs.
Curriculum and Core Coursework
By way of example, a selection of the coursework that can be expected within the Master’s program of study is listed below:
- Algorithms and Computational Geometry
- Advanced Statistical Methods
- Scripting Languages
- Database Concepts
- Artificial Intelligence
- Applied Multivariate Analysis
- Models of Computation for Massive Data
- Big Data Strategy
- Predictive Analytics
- Business Intelligence
- Prescriptive Analytics
- Data and Text Mining
- Decision Theory and Business Analytics
- High-Performance Computing and Parallelization
Key Competencies and Objectives
After completing coursework and obtaining a Master’s degree in data science, graduates will be prepared to successfully navigate a career as a data scientist, competent in the following skills:
- Network/cyber security
- Data collection, analysis, and real-time application
- Data mining
- Database queries and management
- Data cleansing
- Programming languages, such as Python, R, and SAS
- Database queries
- Statistical research
Career Opportunities for Data Scientists in Utah with Advanced Degrees
Jeff Philips, Assistant Professor of computer science at the University of Utah and coordinator for the university’s new graduate certificate in big data, affirmed that big data is also big business. “We’re seeing a revolution in the availability of data,” Philips said. “It’s easy to collect information, but processing and analyzing large stores of data is becoming increasingly difficult. We are at the point where the traditional analytical tools for attacking this problem are breaking down.” Because of this, business owners and CFOs in Utah are actively seeking qualified data scientists with the ability to meet the data influx head-on, and the current job market reflects it.
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 Utah in March 2016.
Senior Statistical Data Analyst, Intermountain Healthcare, Salt Lake City, UT
- Produce analytical solutions (insights, statistical analysis, and models, etc.) for leadership and stakeholders across the organization that supports business or clinical initiatives
- Provide consultation and support in the development, analysis, interpretation, and management of a variety of highly complex data sources
- Support process improvement, operations, strategy, cost reduction, and increased patient safety and satisfaction
Data Scientist, Productive Data Solutions, Inc., Salt Lake City, UT
- Maintain and refine existing engineering applications with the focus on science-driven programs (network optimization models, etc.)
- Extract, consolidate, compile data from various data sources
- Conduct ad-hoc data analyses to provide decision support to business users
- Develop proprietary automation and decision support tools as needed
- Gather requirements related to analytical needs from end users
- Present analysis findings and/or recommendations to business users including senior executives
- Help Director of Engineering identify and prioritize “big rock” projects
- Coach junior team members and help them build data analysis skills
Data Scientist, New Paradigm Group, Salt Lake City, UT
- Leverage advanced statistical analysis, experimental design methods, optimization techniques and predictive model development for data driven decision making
- Develop and apply algorithms, models, and machine learning to key business metrics with the goal of improving operations or answering business questions
- Ensure high data query quality and reliable insights
- Employ program language/coding for applied mathematics
- Apply analytic acumen and a breadth of tools and data sources to answer a wide range of impactful business questions
- Evaluate and recommend third-party analysis tools for potential adoption
- Perform hands-on data analysis and modeling with large data sets
- Use techniques from statistics, machine learning, and other data sciences to estimate predictive models from numeric, categorical, textual, geographic, and other data features
- Develop graphs, charts, plots, maps, etc. to communicate complex information and ideas visually
- Discover data sources, work with Information Systems and others to get them ETL and model ready