Home to 36 Fortune 500 companies and countless startups, Illinois is among the top states in the U.S. when it comes to jobs for qualified data scientists. With teams of analysts turning the terabytes of data that come spiraling out of financial services firms and investment banks, healthcare providers, and every other kind of major industry into actionable business intelligence, Crain’s Chicago Business wasn’t just bragging when it referred to Chicago as the top big data hub in the U.S. behind only Silicon Valley, Seattle and New York.
- 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
From its headquarters in Northbrook, Allstate Insurance has been marshalling the power of big data to reduce costs and create innovative solutions. According to Fortune, in recent years, the company identified hundreds of cases of insurance fraud through deep claims history analyses, and put predictive algorithms to work to cut down on unnecessary home inspections, reducing the number by 20% and saving the company some $3 million.
And outside the city, industrial juggernauts like Caterpillar Inc. in Deerfield and Deere & Company in Moline are turning data scientists loose on every aspect of their businesses, providing all kinds of opportunities for qualified analysts who might be more interested in how big data plays a role in everything from industrial supply chain management to agriculture.
In the public sector, the city of Chicago has put a team of data scientists to work to improve the efficiency of a number of city-run operations, and is passing on the benefits of what they learn. Municipal government has plans to make the city’s databases accessible to the public and create a suite of business intelligence tools accessible to small businesses, while also offering solutions for enterprise data management.
Preparing for a Master’s Degree in Data Science in Illinois
As the field of data science grows at an unprecedented rate, a master’s degree is the standard for gaining the advanced skills sought after by global powerhouses and cutting-edge startups alike. But the admissions process can be highly selective, with schools considering past education, work history, and entrance exam scores.
Undergraduate Degree and Master’s Prerequisite Courses
To earn admission to a graduate school offering data science programs, you will typically be expected to meet the following undergraduate requirements:
- Earn a 3.0 GPA or higher during undergraduate studies
- Possess a bachelor’s degree in a field like computer science, engineering, applied math, or statistics
- Complete prerequisite courses, which typically include the following:
- Calculus I & II
- Linear algebra
You’ll also need a 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
If you want to land on the top of the stack when the selection committee is reviewing applications, then there is no substitute for 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 demonstrate the kind of strong communication skills that are critical in conveying the results of data science efforts.
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, you 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 also tend to give extra consideration to applicants who have demonstrated exceptional quantitative and analytical reasoning capabilities and strong communications skills through work experience. Data science is a rapidly evolving field, and sometimes the most cutting-edge insights come directly from the coal face rather than cold academic assessments. 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
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
Using a Data Science Bootcamp in Chicago or Online to Prepare for a Master’s Degree or to Transition Straight Into a Job
Bootcamps are hardcore, compressed, real-world data science training that happens in a short timespan of between one and nine months. They usually focus on working with real-world data, and use tools and techniques that are actively in play in the industry, with less time spent addressing the theoretical world of data analysis and more focus on results.
As a less expensive and more focused option than other courses of preparation, bootcamps have typically been offered by private training companies. They’ve become so popular, however, that many big-name universities are getting in on the trend, including Chicago’s Northwestern University.
At the Northwestern Data Science and Visualization Bootcamp, students get an immersive 24 week course, conducted on evenings and weekends, that puts them through essential aspects of data science including:
- Data visualization with Tableau, HTML, and CSS
- Data storage in SQL and Hadoop stores
It’s all done with data sets drawn from industries like finance, healthcare, and government to give you real experience in the challenges of real-world quantitative analysis. You have the support of a comprehensive tutor network and one-to-one career coaching and portfolio and resume reviews to help you land a job in the field if going on to a master’s is not in your immediate plans.
Other bootcamps cater to more advanced users, but you can get into Northwestern’s with only a phone interview and a critical-thinking and problem-solving assessment if you are 18 and have at least a GED. It’s a solid course in the fundamentals to get your skills ramped up for a data science master’s degree, or to make the transition directly into a data science job in the field.
Bridge Courses and Massive Online Open Courses (MOOCs) for Applicants Who Do Not Meet Admission Criteria
Another route to beefing up your skills before enrolling is to proactively enroll in relevant MOOCs, or to participate in bridge courses offered by the school itself as a precursor to graduate-level coursework.
Bridge courses are either current or specially designed college classes that can help you fill gaps in functional knowledge that the master’s program will demand. They usually cover topics such as:
- 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 who 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, although many are backed by large universities and offer identical coursework to some of their most popular classes. MOOCs are a good choice for self-motivated, self-studiers who want to pick and choose their coursework before applying to master’s programs.
Earning a Master’s Degree in Data Science in Illinois
Master’s programs in data science offer both classroom-based 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 the advanced degrees required to become job-ready through a more flexible format.
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—and a professional portfolio of completed projects—before graduating.
Key Competencies and Objectives
Students who graduate from a master’s program in data science possess diverse, in-demand skill sets. These are the key factors that employers will be looking at when they evaluate you after graduation. Typically, students develop proficiency in areas including, but not limited to:
- Database queries
- Hash algorithms, cyphers, and secure communications protocols
- Data survey analysis
- Interpretation, visualization, and communication of results
- Sophisticated data analysis
- 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 penetrate 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 are driving what Crain’s called the “hottest job in Chicago tech today,” with employers binge-hiring data scientists in an effort to get ahead of the market.
In 2019, the Harvard Business Review highlighted how far in this direction traditional Illinois companies like John Deere have taken this trend. Capitalizing on new data technologies to meet increases in worldwide agricultural demands due to population growth, Deere employs an “Intelligent Solutions Group” that actively works to increase robotic technologies designed to make farming more efficient and cost-effective.
Civis Analytics, in Chicago, backed by former Google CEO Eric Schmidt and founded by Barack Obama’s one-time Chief Analytics Officer, Dan Wagner, 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.
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.
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.