Qualified data scientists in the Midwest are so hard to find that Seth Dobrin, chief data analyst at agricultural giant Monsanto, likened them to “unicorns” in a 2015 LinkedIn article. Even with this scarcity, however, companies in Iowa across several major industries are looking to big data more than ever to increase efficiency and maximize profits. As a result, data scientists are now, and will continue to be, among the most sought after professionals in the state.
- 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
Agriculture is just one industry in Iowa that will be significantly impacted by the application of data science in the coming years. The Cedar Rapids Gazette described the future of “big ag data” as “drones flying over farm fields recording high resolution images and field sensors providing real-time information on crop nutrients and conditions.” The use of these unmanned aerial vehicles will lead to unprecedented data aggregation, undoubtedly creating increased opportunities for data scientists in Iowa.
Beyond agriculture, data scientists in Iowa will continue to bolster the state’s strong manufacturing sector through innovative strategies and solutions. According to the Iowa Area Development Group, manufacturing accounts for 88 percent of Iowa’s total exports, with billions of dollars of manufactured goods being produced every year. Master’s-educated data scientists play an integral role in manufacturing companies, developing cost-saving initiatives from the machine level to organization-wide practices.
Preparing for a Master’s Degree Program in Data Science in Iowa
A master’s degree in data science gives professionals a competitive edge over their peers when applying to the highest paying jobs, creating a tremendous demand for graduate programs in the field. As a result, admission to these programs is very selective, with schools considering performance on entrance exams, past education, work history, and proficiency in a variety of areas related to the field.
Undergraduate Degree Requirements and Prerequisite Courses
To be considered for admission to master’s programs in data science, applicants would typically be expected to meet the following undergraduate requirements:
- Applicants must earn a minimum of a 3.0 GPA during undergraduate studies
- Applicants must possess a bachelor’s degree in a field such as computer science, applied math, statistics, or engineering
- Applicants must complete prerequisite courses, which typically include the following:
- Calculus I & II
- Linear algebra
Applicants must be able to demonstrate working knowledge of fundamental concepts in the following areas:
- Data structures
- Algorithms and analysis of algorithms
- Linear algebra
Preparing for Success on the GRE/GMAT Exams
Master’s in data science programs typically seek applicants who have scored in the top 15% of the quantitative reasoning section of the GRE or GMAT. Admissions offices may also consider an applicant’s scores in the verbal and writing sections given the importance of communication skills in the field of data science.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:
- Algebraic topics such as functions, linear equations, algebraic expressions, quadratic equations, and graphing
- Arithmetic topics such as integers, roots, exponents, and factorization
- Geometry topics including the properties of triangles, circles, quadrilaterals, polygons, and the Pythagorean theorem
- Data analysis, including topics such as statistics, graphs, Venn diagrams interquartile range, standard deviation, probabilities, permutations, and tables.
To prepare for the GRE, students may take two sample tests by downloading a free program through Educational Testing Service (ETS). Additionally, students may sign up with the Princeton Review to take a practice exam.
GMAT – The quantitative section of the Graduate Management Admissions Test (GMAT) consists of 37 questions that evaluate students’ data analytics skills, particularly in the areas of problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through Veritas Prep and the Princeton Review.
Prior Relevant Work Experience
Admissions department may give top consideration to applicants who have demonstrated exceptional quantitative and analytical reasoning abilities and strong communications skills through their professional work. Among the professional skill sets considered are:
- Communication skills
- Programming proficiency in languages such as JAVA, C++, and Python
- Hacking skills
- Database administration proficiency
- Coding skills
- Total relevant work experience (five years is preferred)
- Data mining ability
Just a few examples of positions and companies in Iowa that would satisfy work experience include:
- Data analysis at A.Y McDonald Manufacturing Company
- Data management at one of the Mercy Medical Center locations
- Cyber security at Dubuque Bank and Trust
Bridge Courses and Massive Online Open Courses (MOOCs) for Applicants Who Need to Fill Gaps in Knowledge
Students who lack one or more of the qualifications necessary for admission to a master’s program in data science would independently pursue Massive Open Online Courses (MOOCs), while those that have been accepted to the program but need to further develop proficiencies before transitioning to master’s-level courses would take advantage of bridge programs available through schools that offer master’s programs in data science.
MOOCs – Massive Open Online Courses – MOOCs allow students to fill gaps in their knowledge through a blend of online problem sets, interactive user forums, filmed lectures, and more. Students would pursue these courses independently to complete their outstanding requirements before applying to a master’s in data science program.
Bridge Courses – Certain master’s programs in data science offer bridge courses for students who meet all admission criteria other than several basic proficiencies. Serving as a precursor to master’s studies, bridge courses typically last 15 weeks and are offered in one of two focus areas:
- Fundamental bridge programs offer courses in linear algebra, data structures, algorithms and analysis of algorithms, allowing students to earn their outstanding qualifications.
- Programming bridge programs offer courses in programming languages such as JAVA, C++, and Python, allowing students to become proficient in these languages before beginning graduate coursework.
Earning a Master’s Degree in Data Science in Iowa
By offering both curricular coursework and immersion experiences, master’s programs in data science equip students with the skill sets sought after by today’s top companies. Through part-time and full-time learning, students typically earn their degree in 18-30 months. Through accelerated learning formats, students may earn their degree in as little as 12 months.
With no campus-based options currently available in Iowa (2016), prospective graduate students would take advantage of online master’s programs to earn degrees that include:
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MIDS)
Online programs have become the standard path for graduate studies in data science due to their flexible scheduling options, which better allow students to maintain a career while pursuing their education.
Core Curriculum and Immersion
Master’s in data science programs offer a diverse blend of courses that prepare students for the professional opportunities in the field. Just some of the topics these courses cover include:
- Data storage and retrieval
- Information visualization
- Machine learning and artificial intelligence
- Advanced managerial economics
- Scaling data – macro and micro
- Quantifying materials
- Data research design and applications
- Network and data security
- Ethics and law for data science
- Statistical sampling
- Data mining
- Experimental statistics
- Visualization of data
- File organization and database management
- Applied regression and time series analysis
- Experiments and causal inference
Master’s programs in data science also require students to complete an immersion experience – a team-based project that simulates real-world data application. Through these projects, students apply their knowledge and talents in collaboration with their classmates and professors.
Key Competencies and Objectives
Upon graduation from master’s programs in data science, students be proficient in skill sets including, but not limited to:
- Interpreting and communicate results
- Developing innovative design and research methods
- Conducting database queries
- Familiarity with hash algorithms, cyphers, and secure communications protocols
- Working within a team setting
- Conducting association mining and cluster analysis
- Survey data analysis
- Developing and conducting sophisticated data analyses
- Using programing languages such as GitHub, SAS, Python, and Shiny by Rstudio
Career Opportunities in Iowa for Data Scientists with Advanced Degrees
The shortage of data scientists in Iowa and the increased use of big data by the state’s farming and manufacturing industries has led companies to actively compete for qualified talent.
Just one Iowa company using data science to create cost-effective strategies and solutions is Johnston-based DuPont Pioneer. The agricultural powerhouse employs data scientists to create data-driven farming technologies that allow farmers to use real-time data in areas ranging from tillage to water use. With access to these technologies, farmers can work more efficiently, leading to massive reductions in costs for the company.
In addition to the opportunities for data science in the commercial sector, several Iowa universities are employing data scientists to further school-wide use of big data and to conduct research on university projects that receive outside funding. For example, in April of 2015, Iowa State University launched a seed funding program designed to establish interdisciplinary research teams to advance big data at the university.
(The following job listings for data scientists in Iowa were surveyed in February 2016 and are shown for illustrative purposes only. They are not meant to represent job offers or provide any assurance of employment.)
Principal Data Scientist at Rockwell Collins in Cedar Rapids – This role would consist of working within a business analytics team to establish strategies and solutions through the use of massive data volume. Rockwell Collins is a $4.6 Billion company with 20,000 employees.
Data Scientist/Computational Scientist at University of Iowa’s Information Technology Services in Iowa City – This technical role would consist of working with University of Iowa researchers on projects and grant opportunities related to the following areas:
- Big Data