As companies increasingly rely on Big Data to help them compete in the global marketplace, they need professionals with the skills to work with data and the business acumen to apply the results to their operations. As the New York Times pointed out in 2012, there is already a shortage of data scientists and business analysts to work with Big Data.
- 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
Analysts expect the shortage to get even worse, and the McKinsey Global Institute predicts that by 2018, there will be a potential shortfall of 1.5 million of managers and workers with the skills to fill the burgeoning data science positions being created.
The shortfall of data scientists is so severe in Ohio that IBM partnered with a local university to establish the IBM Client Center for Advanced Analytics in the Columbus suburb of Dublin. IBM senior vice president Michael Rhodin told the New York Times in 2012 that the impetus for the center came from the needs of its clients—major corporations in Ohio such as Nationwide Insurance, The Limited, Huntington Bank, and Cardinal Health who had difficulty finding data scientists to fulfill their needs.
Along with other major tech companies, IBM is betting that Big Data will be a major trend on par with globalization. Rhodin said “the common language of business is not going to be Chinese or Spanish. It’s going to be math.” Peter Sondergaard, the head of global research for Gartner—a research and advisory firm—relayed the critical need for data scientists in a quote to the New York Times: “data experts will be a scarce, valuable commodity.”
Thus, this is an ideal time for students or working professionals to get the advanced training that will enable them to take advantage of the shortage of data scientists in Ohio. Obtaining a master’s degree provides the skills to launch a high powered career in data science. Ohio offers a large number of opportunities between online data science programs and those located in universities in the state.
Preparing for a Data Science Master’s Degree in Ohio
Students who aspire to be data scientists should being their preparations for a master’s degree while they are enrolled in their undergraduate Bachelor’s science program. Taking appropriate courses and obtaining relevant work experience will greatly improve their chances of being chosen for a data science master’s program.
Undergraduate Degree and Master’s Prerequisite Courses
Graduate schools that offer data science programs are more likely to choose students who have an appropriate background in the quantitative skills needed for this field. Preparing for a data science master’s degree entails:
- A minimum GPA of 3.0
- A Bachelor’s of Science degree in a quantitative field such as computer science, applied math, statistics, or engineering
- Coursework in such key disciplines as calculus I and II, linear algebra, statistics, quantitative methods, and programming languages
Relevant Personal and Work Experience for Admissions
Typically, graduate schools seek applicants with highly relevant professional experience:
- At least five years of technical work experience ideally obtained through employment that demonstrates quantitative skills
- Strong communication skills
- Personal experience related to coding, hacking, data mining, database administration, programming, mathematics, or statistics
Ohio provides a number of options for jobs that may satisfy the requirements for experience. Some of these positions include:
- Data Scientist with Progressive in Mayfield Village
- Data Scientist with Price Waterhouse Coopers in Columbus
- Data Scientist with Securboration in Dayton
Performing high level work with an employer is essential to obtain the strong letters of recommendation required to be admitted into a data science master’s program.
Scoring in the 85th Percentile on the GRE/GMAT Exams
Obtaining a score in the top 15th percent of the GRE and/or GMAT is an excellent way to demonstrate core competency in key data science skills. Advanced preparation for these exams is essential. Both the testing companies themselves and students who have taken these exams strongly recommend taking practice tests on sample quantitative problems until the candidate feels proficient with them.
The GRE’s quantitative section is particularly important and evaluates the candidate’s skills in algebra, geometry, data analysis, and arithmetic. Candidates seeking a career in data science should pay particular note to statistics including probabilities and standard deviations. The official GRE website offers free practice exams and sample questions.
The General Management Admissions Test (GMAT) evaluates a candidate’s quantitative, writing, and verbal abilities. Graduate school admissions departments expect high scores in all of these areas. However, the 37 questions that assess data efficiency and problem solving are particularly important. Candidates can take GMAT practice exams through Veritas Prep and The Princeton Review®.
Bridge Programs and MOOCs (Massive Open Online Courses) to Fill Gaps in Functional Knowledge
Many graduate programs offer bridge programs for candidates who may lack specific skills essential for data science work. Two types of bridge programs are available:
- Programming bridge programs – training in such essential programming languages as JAVA, C++, and Python
- Fundamental bridge programs – courses in algorithms and their analysis, data structures, and linear algebra
An additional way to acquire key skills that a candidate has not learned during his or her experience or education is to take part in Massive Open Online Courses (MOOCs). Such courses are educational programs hosted online designed to supplement the education required to become a data scientist. While many online hosts offer MOOCs, Class Central is a course that is particularly relevant for data scientists wishing to supplement their education.
Earning a Master’s Degree in Data Science in Ohio
Prospective graduate students in data science have a large number of options to choose from in Ohio. The state’s rich academic diversity provides a number of local master’s programs, while residents of Ohio can also avail themselves of the high-quality education available online. Obtaining a master’s degree in data science should open up a wealth of opportunities in Ohio’s extensive business community.
Data Science Programs Available From Ohio Schools
These master’s levels data science programs are available from schools in Ohio:
- MBA in Business Analytics (Online)
- MS in Analytics
- MS in Applied Statistics (specialization in Business Analytics)
- MS in Business Analytics
- Graduate Certificate in Data Science
- MS in Management – Business Analytics
- MS in Health Informatics
- Graduate Certificate in Advanced Business Analytics
- Graduate Certificate in Strategic Business Analytics
- Master of Applied Statistics
- Master of Public Health in Biomedical Informatics
- MS in Digital Science – concentration in Data Science
- MS in Analytics
Online Data Science Programs For Ohio Residents
In addition to the data programs offered by state and private schools in Ohio, students have a number of options to obtain a master’s degree in data science from highly respected online programs.
Such programs offer greater flexibility to working professionals and are offered in a variety of options ranging from accelerated to part-time programs. These programs range from as little as 12 months for accelerated programs to 32 months for part-time study. A graduate student studying full-time can expect to graduate in 18 months.
In addition to the initial online coursework, most graduate programs require that their data science students spend their final semester on campus. Such immersion programs involve intensive classes on campus and the opportunity to network with professors and peers.
Degree programs available include:
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MIDS)
- Online Certificate in Data Science
- Data Mining and Application Graduate Certificate
Core Curriculum Content
While the specific courses required will vary in different Master’s programs, the core courses will cover the essential skills required for data science positions. All programs will include these topics:
- Network and data security
- File organization and database management
- Information visualization
- Quantifying materials
- Statistical sampling
- Experimental statistics
- Applied regression and time series analysis
- Experiments and casual inference
- Machine learning and artificial intelligence
- Data storage and retrieval
- Data research design and applications
- Data mining
- Scaling data – macro and micro
- Advanced managerial economics
- Ethics and law for data science
Most online data science programs provide the opportunity for students to apply their academic training to real-world problems during their immersion experience. Students get the chance to work in small teams and spearhead a data science project. Often, these projects involve data science solutions for local companies.
Key Competencies and Objectives
Master’s programs in data science equip their graduates with a breadth of proficiencies in a number of core areas:
- Programming languages such as Python and C++
- Ethics, privacy, and relevant law
- Data mining and machine learning
- Data and network security
- Data collection and analysis
- Data cleansing
- Database management and file organization
- Statistical sampling
- Research design
- Communication and visualization
Career Opportunities for Ohio Data Scientists with Advanced Degrees
Graduates of data science Master’s degree programs in Ohio have a wide breadth of opportunities for employment. Large companies almost universally employ data scientists. As of 2012, Ohio was home to 57 Fortune 1000 companies and 27 Fortune 500 ones.
In addition, Ohio offers career opportunities with highly specialized data science companies that need data scientists with advanced expertise. For example Soothsayer Analytics in Dublin only employs data scientists with master’s or doctoral degrees.
This company synthesizes design & data science using AI to predict the future of its clients and identify opportunities for optimizing outcomes. Its data scientists are well versed in innovations such as Natural Language Processing, Meta-model Based Simulations, and Deep Learning and actively conduct R&D.
Another high powered Ohio data science company is Cleveland’s Advance Ohio. This firm specializes in creating data systems to help business understand and predict consumer behavior patterns using these techniques:
- Statistical Modeling
- Data Monetization
- Consumer Data Analytics
Advance Ohio utilizes demographic data on 4.7 million households and more than 140,000 business establishments in the state.
To illustrate the breadth of data science job options in Ohio, job listings for some of the many jobs available were compiled in March 2016. These listings are informational only and should not be construed as current job offers or an assurance of employment.
Watson Health – Data Scientist, Analytics with IBM in Cleveland – This position involves creating new data-driven techniques and requires basic knowledge in Python, Java, and SQL along with machine learning, data manipulation, and statistical packages in R and/or Python. One year of experience in each of these areas is required. Applicants with a Master’s degree are preferred.
Data Scientist with Mobile Defense in Cleveland – The individual chosen for this position will join a team and work as a data researcher and software engineer. Applicants must have 2+ years of experience with Java development, a working knowledge of Matlab, SAS, or R, and familiarity with SQL and relational databases. This company desires that applicants have experience with Hadoop and Amazon EMR. Applicants must have an MS or PhD in a relevant technical field.
Senior Data Scientist with ADP in Findlay – Applicants who can work with large amounts of real data with R, SQL, or other statistical packages are preferred. A strong knowledge of SQL query is considered a plus. Another preferred qualification is strong experience with applied statistics and defining key business metrics. A Master’s degree in information science, business analysis, engineering, business administration, or a related field is preferred.
Marketing Data Scientist Manager with JP Morgan in Columbus – This position combines problem solving and client interaction with cross-LOB analytical insights and reporting solutions. JP Morgan desires candidates with 5+ years of analytical and reporting experience and requires proficiency in standard data mining and analytical methods with SAS experience preferred. In addition, candidates should know how to perform time series analysis and have demonstrable experience in applying comprehensive factor analysis. Applicants should also have a technical understanding of data extraction, transformation, and load processing. A Master’s degree in statistics, math, engineering, or the sciences is preferred.
Data Scientist with Parker Hannifin Corporation in Cleveland – The individual will use data mining and modeling techniques to address tactical and strategic business programs that help drive growth. Qualifications include experience in feature engineering, data mining, machine learning, and regression analysis in a business setting. The applicant must be proficient in Java, SQL, statistical software (Python, R, and Stat) and be comfortable working with large data sets of varying quality to solve business needs. A Master’s degree in data science, statistics, BI, econometrics, physics, or mathematics is preferred.