The New York Times recently reported that the data science field has revolutionized the way many industries do business. Healthcare, government, academia, and retail are only a few of the many industries taking advantage of the skills and training possessed by data scientists. In fact, Glassdoor has named data science as the best job in America for this year.
By 2018, it is estimated that over 4 million data science jobs will be created in the United States. According to the McKinsey Global Institute, there are currently far more job openings than there are actual data scientists. Due to the extremely high demand for educated data scientists, the minimum experience requirement for data science jobs has been decreased from a median of ten years to six years experience, making jobs more accessible to recent graduates. Salaries in this field are highly competitive, and they are on average much higher than in all other computer programming, statistics, and analytics-based careers.
Data scientists in Wyoming work in various industries. These trained professionals are currently employed by the University of Wyoming, the Wyoming Game and Fish Department, large accounting firms, and prominent computer network security companies. These companies utilize the skills of data scientists to analyze big data, pinpoint and solve problems, increase revenue, and streamline their businesses.
Preparing for a Master’s Degree in Data Science
As the demand for educated professionals in the data science field rapidly grows, there are numerous new graduate programs being created to prepare students for work in this industry. There are many steps students can take in order to best prepare themselves for a master’s degree and career in data science.
Undergraduate Degree and Master’s Prerequisite Courses
Undergraduate students looking ahead to a master’s degree should use their undergraduate education as a foundation for a graduate degree. Applicants should expect to see the following as common requirements for admission into a graduate degree program in data science:
- At least three letters of recommendation
- The completion of an undergraduate degree program in a quantitative field like mathematics, computer science, programming, engineering, or statistics
- Undergraduate GPA higher than 3.0
- Completion of undergraduate courses in topics like advanced mathematics, linear algebra, computer programming, calculus, statistics, and other relevant prerequisites
Relevant Personal and Work Experience
Graduate programs typically look for candidates who have some experience in the field of data science or a related field. Ideal program candidates typically possess the following:
- At least five years of professional experience in the data science, analytics, information technology, or programming field
- Basic knowledge of programming languages
- Understanding of fundamental concepts like linear algebra, algorithms, and data structures
- Other experiences that exhibit proficiency in computer programming, hacking, coding, database management, big data, data mining, or mathematics
Candidates can utilize bridge programs, MOOCs, and the GRE or GMAT exams to become proficient in subjects related to data science.
GMAT/GRE Scores – Individuals applying for data science graduate programs will almost always be required to take the GMAT or GRE exam. In order to gain admission into the program, students must be able to exhibit strong scores in the verbal and writing portions of the exam. They also must earn a score in the top 85th percentile of the exam. Free practice exams can be taken online in preparation for the GRE and the GMAT.
Bridge Programs – Students who meet all of the other program requirements but still find they are lacking in certain subjects can take part in a bridge program. Many students may not have extensive experience in one or more subjects like linear algebra or programming languages. These bridge programs are offered by the graduate school in order to help students fill in gaps in knowledge before the graduate program starts.
MOOCs – Massive Open Online Courses, or MOOCs, are another way for students to catch up on subjects in which they may not feel totally comfortable. These programs are not offered as part of the graduate school, but they can be perfect for those who either need a refresher or a basic understanding of data science fundamentals.
Earning a Master’s Degree in Data Science
Completing a graduate degree program can result in a number of different degrees. The following degree programs can lead students to a career in data science:
- Master of Science in Data Science (MSDS)
- Master of Science (MS) in Business Intelligence & Analytics
- Master of Information and Data Science (MIDS)
- Master of Science (MS) in Business Intelligence
There are currently no campuses in Wyoming offering graduate degree programs in data science. This can be expected to change within the next few years as the field of data science becomes more and more essential to the business world. Until then, students in Wyoming have many online programs that are available to them. Choosing an online graduate degree program can be a great choice for those who don’t live near campuses offering data science programs and for those who desire a flexible course schedule.
Data science programs are typically comprised of about 32 credit hours. Fulltime students are able to earn their degrees in between 18-24 months. For students who wish to complete their degree more quickly, there are options available that allow them to complete an accelerated program in 12 months. On the other hand, students who may already be working fulltime may wish to only take one course per semester. For these students, there is a part-time option that must be completed in no more than 32 months.
Curriculum and Core Coursework
Graduate courses will cover a wide range of topics, including many of the following advanced data science subjects:
- Experimental statistics
- File organization
- Database queries
- Data and network security
- Data visualization
- Advanced coding
- Data mining
- Applied machine learning
- Big data
- Applied regression
- Time series analysis
Many graduate programs will also require students to complete a culminating capstone course at the very end of the degree program. Though most of the course is completed remotely in an online format, students may also take part in an immersion experience. Immersion experiences are commonly offered on a campus and offer students the opportunity to network with other students, meet the faculty, and explore additional learning opportunities.
Key Competencies and Objectives
Graduate programs are planned and operated with the purpose of preparing students for a data science career. These programs instruct students in the newest methods and technologies in order to give them relevant training and experience for their present or future jobs. Upon receiving their master’s degrees, students should become proficient in the following core competencies:
- Statistical analysis
- Visualizing data
- Interpreting and communicating data
- Familiarity with ethical and legal areas of the data science industry
- Understanding of programming languages like Python, SAS, R, GitHub, Shiny, and many others
- Proficiency in cryptology, network security, algorithms, and ciphers
- Data mining and management
- Computer programming
Career Opportunities for Data Scientists in Wyoming with Advanced Degrees
After earning a graduate degree, it is then time to put training into practice. The job market for data scientists in Wyoming is gradually growing, and highly educated graduates are in high demand.
The following job listings have been provided as illustrative examples only, and should not be interpreted as job offers or assurances of employment. These examples were gathered from a survey of job vacancy announcements for data scientists in Wyoming in March 2016:
- Senior Data Analyst with William E. Wecker Associates, Inc. at Jackson – Candidates applying for this role are required to hold a graduate degree or Ph.D. in statistics, applied mathematics, data science, or a related field. Ideally, applicants should be very familiar with SAS, Stat, R, S-Plus, Python, and Mathematica, and other similar packages. The Senior Data Analyst has a wide range of responsibilities including analyzing complex data sets and working with other project managers and consultants to solve problems for clients.
- Data Scientist/Analyst with Cheyenne Regional at Cheyenne – This position is ideal for someone looking to start out in the data science career field. Candidates must have completed a bachelor’s degree in a relevant field and be familiar with data management, analysis, statistics, information technology, and the healthcare system. Ideally, applicants should have two years of experience involving data science.
- Management and Data Science Analyst with U.S. Department of Veteran Affairs at Sheridan – An individual in this role should either have extensive experience in a data science or data analyst position, or have completed at least three years of a graduate level degree program or higher. This role requires the individual to become expertly acquainted with QSV Data Informatics in order to interpret the outcome information related to the Veterans Affairs Healthcare Department.