Qualified data scientists provide companies with innovative, cost-saving solutions and strategies, making them among today’s most sought after professionals in a variety of industries. Tech recruiting firm DICE found that data engineer positions grew by 50% between 2019 and 2020, and positions for senior data scientists grew by 38%, accounting for two slots among the top three hottest tech professions in the country right now.<!- mfunc feat_school ->
That’s as true in Indiana as elsewhere, and it shows up in a big way in a couple of the state’s major industries:
Healthcare – According to the McKinsey Global Institute, big-data strategies that are used to inform decision making could generate up to $100 billion in value annually across the U.S. healthcare system. A 2018 deal between the Regenstrief Institute of Indianapolis and MDClone in Israel promises to use data science to make medical data available to researches faster, all while ensuring patient privacy. Indiana is also home to health insurance juggernaut Anthem, a company that employs 63,900 people.
Automotive – Auto component manufacturing is also well within the sphere of big data, and is particularly reliant on real-time data streaming. According to the IBM Big Data and Business Hub, “the growing use of telematics and other sensor technologies is changing the way automotive and manufacturing companies approach their customers and their business strategies.” Indiana is home to automotive manufacturing giants Thor Industries (17,800 employees) and Allison Transmission Holdings (2,600 employees), each of which are Fortune 1000 companies that have been adding data scientists to the payroll faster than any other profession.
Preparing for a Master’s Degree in Data Science in Indiana
Master’s degree programs in data science can be highly competitive, with schools giving a lot of weight to applicants’ past education, professional experience, their functional proficiency in programming and applied math, and entrance exam scores. If data science jobs are hot, slots in top-end universities are even hotter, so you should expect to have to lay some solid groundwork before being accepted to a data science master’s program here in Indiana.
Undergraduate Degree Requirements and Prerequisite Courses
To be considered for admission to a master’s program in data science, you’ll have to do well at the bachelor’s level first. The type of degree you earn is important, as are the specific courses you take, and how well you do in them:
- Bachelor’s degree in a relevant quantitative field such as applied math, statistics, computer science, or engineering
- Prerequisites in programming languages, linear algebra, statistics, calculus I and II, and quantitative methods
- Minimum GPA of 3.0
How to Prepare for the Quantitative Reasoning Section of the GRE/GMAT Exams
Your scores on the quantitative section of the GRE or GMAT are strongly considered by master’s programs admissions offices. Students who score in the top 15% on this section are typically given top consideration for admission. Programs may also give weight to an applicant’s scores on the verbal and writing sections of these exams since strong communication skills are such a vital part of presenting data science findings.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following subjects:
- Algebraic topics, including linear equations, functions, graphing, algebraic expressions, and quadratic equations
- Arithmetic topics, including roots, exponents, integers, and factorization
- Geometry topics such as the Pythagorean theorem and the properties of triangles, circles, quadrilaterals, and polygons
- Data analysis, covering topics including interquartile range, standard deviation, statistics, graphs, Venn diagrams, probability tables, and permutations
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. To prepare for the GMAT, students may take practice exams through Veritas Prep and the Princeton Review.
Relevant Personal and Work Experience
Top master’s programs don’t just look at your academic performance, however. They also want to evaluate your personal qualities, and actively look for candidates who have demonstrated some sort of real-world aptitude in programming or data analysis. Schools typically consider the following when reviewing applications:
- Coding skills
- Total relevant work experience (five years is preferred)
- Data mining ability
- Database administration proficiency
- Communication skills
- Programming proficiency in languages such as JAVA, C++, and Python
Just some of the jobs through which graduate students develop these basic competencies in Indiana include:
- Cyber security at Anthem
- Working with data management at Berry Global
- Statistical analysis at Kar Global
Building Your Master’s Application or Finding Employment With a Data Science Bootcamp in Indianapolis or Online
Data science bootcamps represent a new option on the playing field for anyone interested in getting into either a data science career, or building up their qualifications for a master’s program. Bootcamps are high-intensity, relatively low-cost, practical programs designed to take individuals from a certain base level of knowledge up to a level of capability that can actually land them a job in data science.
Different bootcamps have different entry points and are focused on different levels of education. For a master’s program prep, you will probably want to look for something at the low end, or entry level, and the Butler University Executive Education Data Analytics Boot Camp fits the bill.
Many bootcamps are offered by private providers, but when you can find a 24-week, part-time program offered by a prestigious university like Butler, it’s worth a second look. Available either on-site in Indianapolis or online, as an increasing number of bootcamps are, Butler’s focus on executive education emphasizes hands-on use with common data analysis tools such as:
- API Interactions, SQL, Tableau
As with all bootcamps, it focuses less on theory and more on practical education and outcomes. That means you work primarily with real-world data, on the kind of problems that data scientists are actively solving in the workplace today. A broad network of expert tutors is available for expertise on-tap whenever you need it, and a comprehensive career services setup helps you build out your resume and portfolio to prepare for either job or college applications after you graduate.
Bridge Courses and Massive Open Online Courses (MOOCs) for Applicants Who Need to Bridge Gaps in Knowledge
Even data experts with impressive professional resumes may lack one or more of the qualifications required for admission to a master’s program in data science. To meet these outstanding requirements, you may instead choose to enroll in massive open online courses (MOOCs). Bridge courses are another route, offered by the schools themselves to students that have already been accepted into a graduate program, but who need to become proficient in an area of applied practice prior to beginning graduate courses.
MOOCs – Massive Open Online Courses – MOOCs are offered online and usually in self-paced coursework put together by experts in the field and filled with hundreds or thousands of other students studying at the same time. Many are put together by prestigious universities, and you have the advantage of picking and choosing what subjects you intend to brush up on before you begin your master’s program application.
Fundamental and Programming Bridge Courses – Bridge courses are often available to students that have been accepted into a master’s program in data science, but that need to fill gaps in functional knowledge before transitioning to master’s-level courses. These courses are offered directly through the graduate program and typically take about 15 weeks to complete.
Programming bridge courses are for those that need to become proficient in the mandatory programming languages required to begin the master’s degree program.
Fundamental bridge courses would develop proficiency in the following areas:
- Linear algebra
- Algorithms and analysis of algorithms
- Data structures
Earning a Master’s Degree in Data Science in Indiana
Like most states, Indiana has a growing number of data science master’s degree programs available. However, more and more professionals are pursuing their degree through accredited online programs, allowing them to complete their coursework in a more flexible format, and at a school anywhere in the U.S.
Through these programs, which consist of self-paced coursework, live classes, and an immersion experience, students can earn one of the following degrees:
- Master of Information and Data Science (MIDS)
- Master of Science in Data Science (MSDS)
Through part-time and full-time learning, students typically earn a master’s degree in data science in 18-30 months. Through accelerated learning formats, students may earn their degree in as little as 12 months.
Core Curriculum and Immersion
The courses offered in master’s programs in data science are targeted specifically to meet the demands of Indiana’s top employers. Examples of these courses include:
- Advanced managerial economics
- Visualization of data
- Applied regression and time series analysis
- Machine learning and artificial intelligence
- Data research design and applications
- File organization and database management
- Network and data security
- Experimental statistics
- Ethics and law for data science
- Information visualization
Beyond that traditional coursework, master’s programs in data science require students to complete an immersion experience, which consists of collaborative work on a project designed to simulate real-world data science applications. Through these experiences, students can demonstrate their talent and communication skills before entering the professional workforce.
Key Competencies and Objectives
By the time you complete your master’s program in data science, you will have developed extensive expertise in a number of in-demand areas including, but not limited to:
- Innovative design and research methods
- Association mining and cluster analysis
- Proficiency in programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
- Hash algorithms, cyphers, and secure communications protocols
- Work within a team setting
Moreover, you will have had plenty of opportunities to demonstrate your skills through coursework and lasting projects in your portfolio, which is exactly what potential employers want to see in future data science professionals.
Career Opportunities in Indiana for Data Scientists with Advanced Degrees
With major companies across a variety of industries in Indiana actively competing for the talents of qualified data scientists, the state is among the most promising in the Midwest in terms of employment prospects. Beyond the healthcare and automotive industries, Indiana plays host to a number of successful companies in the transportation industry and the machinery & equipment manufacturing sector. All of those fields are expected to rely significantly on the innovative use of big data in the coming years.
The following job listings were taken from a survey of job vacancy announcements for data scientists in Indiana (examples are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment):
Senior Data Scientist at Adesa Inc. in Carmel – The data scientist’s role would consist of responsibilities including, but not limited to analyzing data sets to provide actionable insights that optimize the company’s business operations; using SQL/Tableau to create reports and data extracts against large data sets; and partnering with various teams within the company to develop innovative solutions.
Data Scientist at KSM Consulting in Indianapolis – The role would consist of developing algorithms and methodologies on structured and unstructured data for on-demand and software-imbedded use, including the application and development of machine learning.
Data Scientist (R Programming) at Net2Source, Inc. in Indianapolis – Within a team setting, the data scientist would be responsible for evaluating and documenting the design and development of various system enhancements as the company prepares to implement the next release of the Modeling and Simulation Explorer (MuSE) system.<!- mfunc feat_school ->