A report released by the McKinsey Global Institute estimates that by 2018 there will be a need for between 4-5 million skilled workers with expertise in high level data analysis nationwide. McKinsey Global Institute even named data scientist “the best job in America for the year 2016.” Data scientists in Wisconsin will find no shortage of opportunities in industries including finance and insurance, healthcare, retail, human resources, marketing, logistics, manufacturing and more.
- 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
Schneider, a Green Bay-based logistics and transportation company, uses the expertise and insights of data scientists in order to create new and innovative solutions. These data scientists develop algorithms and use quantitative reasoning to interpret statistics and analyze large data sets in order to help the company run at optimum efficiency. Rocket Industrial, a small business located in Wausau, uses master’s-educated data scientists to help optimize all areas of the company and increase revenue.
As companies compete for talent, the demand for master’s-prepared data scientists is increasing dramatically. According to Butch Works, an executive recruiting firm, the median annual salary for data scientists is $120,000. This is only fitting, considering that data scientists are helping companies solve complex problems and increase revenue.
Preparing for a Master’s Degree in Data Science
With so many high tech professionals eager to enter the field of data science, new graduate programs are being created to keep up with the growing demand. Students can prepare by making sure they meet the standards that are commonly upheld by graduate program admissions departments in terms of undergraduate education, work experience, functional proficiencies and high scores on entrance exams.
Undergraduate Degree and Master’s Prerequisite Courses
Due to the rigorous nature of these programs, graduate schools often maintain rigorous requirements for admission. In many cases, applicants must meet the following undergraduate requirements in order to gain entry into a data science graduate program:
- Completion of a bachelor’s degree in a quantitative field such as statistics, engineering, computer science, or mathematics
- An undergraduate GPA of at least 3.0.
- Undergraduate courses in related topics like statistics, calculus, and computer programming
- Three letters of recommendation from professional references or undergraduate faculty
Relevant Personal and Work Experience
Graduate admissions departments typically seek applicants who have significant professional experience in a field related to data science. Most programs require the following for entry into the program:
- At least five years of technical work experience
- Significant experience demonstrating proficient quantitative abilities such as data analysis, data management, computer programming, and other related skills
- Basic understanding of programming languages such as R, JAVA, C++, or Python
Graduate program applicants generally come from a professional background in database administration, math/statistics, network security, programming or data analytics.
How to Prepare for Success on the GMAT/GRE Exams
Applicants are expected to achieve high scores (at least in the 85th percentile) on the quantitative reasoning section of the GRE or GMAT exams in order to gain admission into a data science graduate program. Admissions departments also consider strong scores in the verbal and writing sections.
Students may take a free practice test online to prepare for the GRE or GMAT.
Bridging Gaps in Functional Knowledge Through Bridge Courses and MOOCs
Bridge Courses – Students that have been accepted into a graduate program in data science based on having met all enrollment criteria, but who may lack extensive professional experience or education in either fundamental math and statistics or programming, are often given the opportunity to take prerequisites before transitioning to master’s-level coursework. The need to fill gaps in functional knowledge in one or more areas before enrolling in a graduate program is common. These 15-weeek pre-master’s programs would be offered directly through the graduate school.
MOOCs (Massive Open Online Courses) – MOOCs provide aspiring data scientists with the chance to fill gaps in their knowledge through a blend of filmed lectures, online coursework, and student-professor communication. MOOCs are for prospective graduate students who wish to gain the necessary proficiencies before applying to a master’s program in data science and are available completely independent of graduate school.
Earning a Master’s Degree in Data Science in Wisconsin
Currently, there are residential graduate programs in data science available in Madison and Milwaukee. With most students seeking a more flexible program format, online options are even more widely used. A master’s program in data science consists of 30-32 credits and result in degrees with titles that include.
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MIDS)
Curriculum and Core Coursework
Graduate students in data science programs will take courses covering the following topics:
- Analyzing data
- Applied machine learning
- Data visualization and communication
- Research design
- Application for data and analysis
- Retrieving and storing data
- Data mining
- Experimental statistics
- Database management
- Quantifying data
- Managerial economics
- Statistical sampling
Students may also be required to complete an internship, in addition to the requisite group immersion experience, which typically serves as the capstone project.
Key Competencies and Objectives
Graduate programs in data science provide students with a knowledge base they will use to succeed in their future careers. Coursework and immersion experiences are designed to prepare students to become proficient in the following areas:
- Technical skills such as data mining, machine learning, computer programming, management of data, and network security
- Translating data into visualized ideas
- The ability to communicate findings both orally and written
- Interpreting large batches of complex data
- Proficiency in programming languages such as Python, SAS, Shiny, or GitHub
- Understanding of cryptology, hash algorithms, and network security protocols
- Statistical surveys and analysis
Career Opportunities for Data Scientists in Wisconsin with Advanced Degrees
After earning a degree in data science, graduates then have the opportunity to search for a job that will allow them to put their extensive training into practice.
The following job listings have been provided as illustrative examples only, and are not meant to represent job offers or an assurance of employment. These examples were gathered from a survey of job vacancy announcements for data scientists in Wisconsin in February 2016:
Data Science Intern with Land’s End at Dodgeville – This internship allows recent graduates to ease into the data science field. An ideal candidate is required to have a graduate degree in a related field and must be familiar with SQL or another querying languages. The chosen intern will work with developing statistical models, investigating company problems using computer science, and interpreting incoming data.
Data Scientist with Smith & Hanley Associates, LLC at Madison – This position requires the candidate to hold a master’s or Ph.D. in computer science, engineering, math, statistics, or economics. An ideal candidate must have at least five years of fulltime business-related experience in data mining algorithms, neural networks, text, and NLP. Responsibilities include using data to identify patterns and developing solutions to complex company problems.
Data Scientist with Foot Locker at Wausau – Those seeking a data science job in the retail industry can apply for jobs in retail store headquarters like Foot Locker. A data scientist in this role would ideally be proficient in green field product development, API based integration, SAS, Python, SQL, MapReduce, Hive, Pig, and Spark. Candidates must have a master’s degree or Ph.D. in a science or math related field as well as at least 3 years of relevant experience or training.
Enterprise Technology Innovation Data Scientist with WPS Health Solutions at Madison – The data scientist in this position is responsible for presenting new analytics opportunities to enhance the efficiency and value of the company. Ideal candidates have a strong understanding of statistical analysis, predictive modeling, and data visualization and are comfortable managing a high volume of complex data. A bachelor’s degree is required, but candidates with a master’s or higher degree are given preference.
Lead Data Scientist with United Health Group at Wauwatosa – This position requires a graduate degree or Ph.D. in statistics, applied statistics, applied mathematics, or similar quantitative fields. Candidates for this position would ideally already have at least five years of experience working with statistics and data related to the health services industry. Primary responsibilities include providing leadership to other data science department employees, implementing predictive models, and using analytic methods to detect healthcare fraud, waste, abuse, or errors.