Home to 34 Fortune 500 companies and dozens of innovative startups, Illinois is among the top states in the U.S. for qualified data scientists. According to Crain’s Chicago Business, the city of Chicago is “emerging as a data-science hub” and is the “top market behind only Silicon Valley and perhaps Seattle and New York.” Outside of the city, corporate juggernauts such as Caterpillar Inc. in Peoria and Deere & Company in Moline are actively implementing data science into every aspect of their business, providing ample career opportunities for qualified professionals throughout the state.
Allstate Insurance headquartered in Northbrook, is just one major company using data science to reduce costs and create innovative solutions. In recent years, the company has detected hundreds of cases of insurance fraud through massive data analysis using the software platforms Hadoop and Tableau, according to Fortune. Additionally, through predictive algorithms based on historical data, the company has cut down on unnecessary homeowner inspections by 20%, saving some $3 million.
In the public sector, the city of Chicago has employed a data science team to improve the efficiency of a number of city-run operations. Among the goals the city hopes to accomplish through the use of data science in the coming years:
- Make the city’s databases accessible to the public
- Create a suite of business intelligence tools to connect the city’s users
- Deliver options for enterprise data management
Preparing for a Master’s Degree in Data Science in Illinois
As the field of data science grows at unprecedented rates, professionals in Illinois are pursuing a master’s degree in data science to learn the advanced skills sought after by global powerhouses and cutting-edge startups alike. To gain admission, students must meet highly selective requirements, with schools considering applicants’ past education, work history, and competency in a variety of areas related to the field.
Undergraduate Degree and Master’s Prerequisite Courses
To earn admission to graduate schools with data science programs, students would typically be expected to meet the following undergraduate requirements:
- Applicants must earn a 3.0 GPA or higher during undergraduate studies
- Applicants must possess a bachelor’s degree in a field such as computer science, engineering, applied math, or statistics
- Applicants must complete prerequisite courses, which typically include the following:
- Calculus I & II
- Linear algebra
Applicants must have working knowledge of fundamental concepts in the following areas:
- Data structures
- Linear algebra
- Algorithms and analysis of algorithms
How to Succeed on the Quantitative Reasoning Sections of the GRE/GMAT Exams
Applicants can position themselves for top consideration into master’s degree programs by scoring in the top 15 percent of the quantitative section of the GRE or GMAT. Programs may also evaluate applicants’ scores in the Verbal and Writing sections, which can show strong communication skills.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:
- Algebraic topics such as expressions, linear equations, quadratic equations, graphing, and functions
- Data analysis topics such as statistics, interquartile range, permutations, probabilities, graphs, and standard deviation
- Geometry topics including the properties of triangles, quadrilaterals, circles, polygons, and the Pythagorean theorem
- Arithmetic topics such as integers, roots, exponents, and factorization
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 – Consisting of 37 questions, the quantitative section of the Graduate Management Admissions Test (GMAT) is designed to evaluate students’ data analytics skills, particularly in problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through Veritas Prep and the Princeton Review.
Relevant Personal and Work Experience for Admissions
Admissions departments may give top consideration to applicants who have demonstrated exceptional quantitative and analytical reasoning capabilities and strong communications skills through work experience. Relevant skills would include:
- Database administration proficiency
- Total relevant work experience (five years is preferred)
- Data mining skills
- Programming proficiency in languages such as JAVA, C++, and Python
- Coding skills
- Hacking skills
Just a few examples of qualifying work experience and employers in Illinois might include:
- Statistical analysis at The Boeing Company
- Cyber security at Walgreens
- Working in data management at Mondelēz International
Bridge Courses and Massive Online Open Courses (MOOCs) for Applicants Who Do Not Meet Admission Criteria
To obtain any outstanding qualifications required for admission to a master’s program in data science, students may opt to proactively enroll in relevant MOOCs prior to applying. Those that have already gained acceptance into a graduate program based on other merits may participate in bridge courses as a precursor to graduate-level coursework:
Bridge Courses allow students to fill gaps in functional knowledge in the following fundamental areas:
- Programming in languages such as JAVA, Python, and C++
- Data structures
- Analysis of algorithms
- Linear algebra
Bridge courses are made available to students that have met all enrollment criteria and that have been accepted into the graduate program, but that just need to gain proficiency in a particular area before transitioning to master’s-level coursework. Bridge courses are typically completed in about 15 weeks time.
MOOCs – Massive Open Online Courses – allow students to develop diverse new skill sets through a blend of online data sets, filmed lectures, and student-professor communication. MOOCs are offered through industry organizations and are completely separate from graduate school.
Earning a Master’s Degree in Data Science in Illinois
Master’s programs in data science offer both curricular coursework and immersion experiences to provide students with a well-rounded repertoire of skills. Beyond traditional campus-based programs, students may elect to pursue their master’s degree in data science online through an accredited program. By learning online, students can pursue degrees such as the Master of Science in Data Science (MSDS) or the Master of Information and Data Science (MIDS) through a more flexible format, allowing them to maintain their current work hours.
Master’s degree programs in data science available online and at campus locations in Illinois include:
- Master of Data Science–Chicago
- Master of Science (MS) in Data Science–Romeoville
- Master of Science (MS) in Data Science–Elmhurst
- Graduate Certificate in Data Science – Online
- Data Mining and Applications Graduate Certificate – Online
- Master of Science in Data Science (MSDS) – Online
- Master of Information and Data Science (MIDS) – Online
Programs typically offer several learning formats based on students’ needs:
- Part-time: Students typically earn their degree in 30-32 months
- Full-time: Students may earn their degree in 18 months
- Accelerated: Students can earn their degree in as little as 12 months
Core Curriculum and Immersion
To prepare students for the rapidly growing professional data science realm, programs offer courses targeted specifically to meet the demands of the world’s most profitable and innovative companies. Programs typically offer courses that include:
- Applied regression and time series analysis
- Experimental statistics
- Data mining
- Data research design and applications
- Information visualization
- Machine learning and artificial intelligence
- Experiments and causal inference
- Statistical sampling
- Advanced managerial economics
- File organization and database management
- Data storage and retrieval
- Network and data security
- Ethics and law for data science
- Quantifying materials
- Scaling data – macro and micro
- Visualization of data
An important aspect of data science programs is the immersion experience – a collaborative project designed to simulate real-world data application. These experiences provide students with the opportunity to demonstrate their talent in a team-based setting and establish working credentials before graduating.
Key Competencies and Objectives
Students who graduate from a master’s program in data science possess diverse, in-demand skill sets. Typically, students earn proficiency in areas including, but not limited to:
- Database queries
- Hash algorithms, cyphers, and secure communications protocols
- Data survey analysis
- Interpretation and communication of results
- Proficiency in programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
- Sophisticated data analyses
- Innovative design and research methods
- Association mining and cluster analysis
Career Opportunities in Illinois for Data Scientists with Advanced Degrees
As data science continues to proliferate every aspect of big business, Illinois looks to be among the most promising states in the U.S. for qualified data scientists in the coming years. The state’s blend of global powerhouses and promising startups led Gigaom to label Illinois as a “significant data science hiring market.”
According to Data Science Central, Illinois-based agricultural juggernaut John Deere has “embraced big data enthusiastically,” capitalizing on new data technologies to meet increases in worldwide agricultural demands due to population growth. The company employs an “Intelligent Solutions Group” that actively works to increase robotic technologies designed to make farming more efficient and cost-effective.
Civics Analytics, which Built in Chicago named one of “Chicago’s 50 Startups to Watch,” employs data scientists to provide solutions in industries including healthcare, education, media, and more. The company also focuses on building various cloud-based technologies.
The following job listings were taken from a survey of job vacancy announcements for data scientists in Illinois completed in February 2016 (examples are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment):
Computer Vision Data Scientist at CCC Information Services, Inc. in Chicago – The role consists of working with a project team to turn data insights into business recommendations and model the value of insights.
Data Scientist, Supply Chain Management at Sears Holding Corporation in Hoffman Estates – This professional would oversee the development of analytical tools and algorithms to optimize the company’s capacity needs and in-home routing.
Lead Data Scientist/Analytics Expert at Molex in Lisle – The role consists of tasks including, but not limited to, analyzing large data sets related to chemical and petrochemical production sites, deriving conclusions for troubleshooting, and developing models for predictive maintenance purposes.