The big data revolution has brought data scientists to the forefront in key Nebraska industries – everything from finance, healthcare, and transportation, to the military and local government. Smaller tech startups sprouting up in Lincoln – the so-called “Silicon Prairie” – like Bulu Box and Opendorse, are also helping to drive the demand for data scientists in that area.
Doing everything from computer model development to finding new ways to obtain information, data scientists are now found working everywhere from municipal government agencies to the state’s largest corporations.<!- mfunc feat_school ->
First Data Corporation, the nation’s largest payments industry company, operating in Omaha, uses data scientists to efficiently process merchant payments from over six million clients. In this capacity, data scientists also develop models and algorithms to help First Data clients improve their marketing effectiveness, mitigate risk, detect fraud, and optimize decision-making.
With more than 540,000 rail car trips either originating or terminating in the state in 2017, Nebraska is home to the largest railroad classification yard in the world; Bailey Yard in North Platte. Data scientists create models that analyze rail delays, cargo weight, personnel availability, weather, and other factors to determine the most efficient means of organizing rail freight.
The requirements for working in the field are high, with companies recognizing the skills that come with earning a master’s degree in data science as being foundational. And with the increasing interest in the field, getting into one of these programs has become just as challenging.
Preparing to Enroll in a Master’s Degree Program in Data Science in Nebraska
As one of the hottest fields in the nation, data science is also one of the most sought-after concentrations at the graduate level. As such, master’s programs have high standards for their prospective students in terms of undergraduate education and prior work experience.
Undergraduate Degree and Master’s Prerequisite Courses
Your preparation for a data science career will start at the undergraduate level. The minimum requirements for data science graduate programs typically include:
- Bachelor’s degree in a quantitative field like applied math, computer science, statistics, or engineering
- Minimum GPA of 3.0
Prerequisite courses cover subjects such as:
- Calculus I and II
- Quantitative methods
- Linear algebra
- Programming languages like Java and Python
Relevant Personal and Work Experience
Academic experience is only one aspect of what it takes to impress an admissions committee, though. Work or relevant personal experience are also strong qualifiers. As a condition of entry, most graduate programs require applicants to come from a background that includes:
- A minimum of five years of professional experience that involves quantitative reasoning
- Work experience that demonstrates abilities in coding, math, statistics, or database administration
- Demonstration of analytical reasoning ability
- Some experience with data structures, algorithms, and analysis of algorithms
Local examples in Nebraska of relevant work experience can include:
- Working at Offutt Air Force Base in a capacity that involves data such as supply management, computer security, or logistics
- Working at any of Nebraska’s healthcare providers, such as CHI Health or the Methodist Health Center in Omaha, using data to improve patient outcomes or logistics efficiency
- Working with First Data Corporation to improve operations or provide customer service related to data processing
- Working at Union Pacific Railroad’s headquarters in Omaha to direct freight or sort cars in North Platte’s Bailey Yard
Demonstrating Proficiencies with High Scores on the GRE/GMAT Exams
Graduate schools will often require their applicants to score in the top 15% of all test-takers. While scoring well on the quantitative section of these exams is vital, the importance of good communication skills in data science also means that applicants should score well on the verbal and writing sections. Don’t slack off in your test prep on any area of these critical exams.
The quantitative reasoning section on the Graduate Record Exam (GRE) revised general test evaluates the following:
- Arithmetic topics including integers, factorization, exponents, and roots
- Algebraic topics such as algebraic expressions, functions, linear equations, quadratic equations, and graphing
- Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem
- Data analysis, covering topics like statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
Students can prepare for the GRE by reviewing Educational Testing Service’s (ETS) Math Review, as well as GRE practice exams provided by the Princeton Review and Veritas Prep.
The Graduate Management Admissions Test’s (GMAT) quantitative section evaluates students’ skills in data analysis. One of the four main sections of the GMAT, the quantitative portion is comprised of 37 questions to be completed in 75 minutes. All of these questions pertain to data sufficiency and problem solving. GMAT practice exams can be found through the Princeton Review and Veritas Prep.
Online Data Science Bootcamps to Prepare For a Master’s Program While Becoming Job-Ready
If you think you can keep up, a data science bootcamp offers some excellent preparation for a master’s degree program, or for transitioning straight into your career. While traditional degree programs offer a measured, comprehensive, strongly theoretically supported education in data science, bootcamps take another approach: in a few weeks or a few months, they jam in as much practical, hands-on data science skill training as possible, focusing on the development of those skills as the final result more than credits and grades.
While that leaves some blanks on the map of your understanding of the how and why of data science, it gives you firm grounding in the what and how as you learn real-world skills using the same tools and techniques that are being used every day out in the field.
It all happens as part of a cohort of fellow students, supported by instructors who typically have plenty of real-world experience of their own. You will work through a series of projects that teach you technologies like:
- R and Python programming
- Hadoop and other Big Data stores
- SQL and database engines like MySQL
- AI and machine learning algorithms
- Data visualization tools like Tableau
While most bootcamps were started as small private efforts, larger and better-supported university programs are now starting to come to the forefront. Many of these are available online in Nebraska, including:
- Northwestern Data Science and Visualization Boot Camp
- Rice University Data Analytics Boot Camp
- The Data Analysis and Visualization Boot Camp at Texas McCombs
- University of Minnesota Data Visualization and Analytics Boot Camp
As part-time, evening and weekend programs, these are longer than average, clocking in at six months. But they also come with the kind of instructors and resources that smaller programs have difficulty matching, including in-depth career services departments with dedicated coaching and portfolio-building services… just the thing for getting your master’s application in shape.
Bridge Programs and Massive Open Online Courses (MOOCs) to Qualify for Master’s Programs
Data science master’s programs require enrolling students to have a good understanding in a diverse set of skills. To supplement an applicant’s bachelor’s education, data science graduate programs may require some newly admitted students to complete a bridge program in an area where their academic record is lacking. Bridge programs are normal university undergraduate courses or a series of courses in a specific subject, usually offered over a summer to give students the opportunity to complete them before their cohort begins the main degree program. Once the bridge program is complete the student can then begin studying the data science graduate core curriculum.
Universities typically offer two types of bridge programs:
- Fundamental bridge programs, covering subjects like linear algebra, algorithms, analysis of algorithms, and data structures
- Programming bridge programs, covering important languages like Python, Java, and C++
MOOCs (Massive Open Online Courses) are an informal way students can add to their credentials. These recorded lectures and sample problem sets are available in an online interactive format that involves fellow students, as well as teaching assistants and sometimes professors. While not recognized as official academic credit, MOOCs can provide students with valuable knowledge in key areas like engineering, mathematics, statistics, and even data science. They give you a chance to study in a more focused way but on a more flexible basis than bridge courses.
Earning a Master’s Degree in Data Science in Nebraska
As big data sweeps the nation, colleges and universities are struggling to offer relevant degrees to meet the growing demand. An expanding number of universities in the state are offering both graduate and undergraduate degrees in either data science or related fields like mathematics and statistics that you can take advantage of.
Nebraska residents also have the option of getting the full advantages of a master’s degree in data science entirely online. Colleges and universities offering their data science graduate programs online also offer a variety of scheduling options:
- Traditional completion time – approximately 18 months or three semesters
- Accelerated completion – completion in as little as 12 months or two semesters
- Part-time – completion in as much as 32 months or five semesters
- Graduate certificates – completion of 12-15 semester credits in one to two semesters
Master’s programs are comprised of around 30 semester credits in total. The types of degree programs can vary from university to university:
- Master of Science (MS) in Data Science
- Master of Information and Data Science (MIDS)
- Master of Science in Data Science (MSDS)
- Data Mining and Applications Graduate Certificate
- Online Graduate Certificate in Data Science
Core Curriculum of a Master’s Program
Master’s-level graduate students cover core curriculum topics that include:
- Information visualization
- Ethics and law for data science
- Machine learning and artificial intelligence
- Data mining
- Data storage and retrieval
- File organization and database management
- Applied regression and time series analysis
- Data research design and applications
Prospective employers and professors also evaluate students on their immersion experience towards the end of the program. The immersion experience involves students grouping themselves into teams to accomplish a project that has real-world implications, and often using real-world data. This is the point where academics meets concrete applications of data science, and is also a chance to demonstrate interpersonal communication and teamwork skills.
Key Competencies and Objectives
Students who earn their master’s degree in data science can exhibit these core competencies and apply them to generate practical solutions:
- Ability to work in teams to achieve specific goals
- Ability to conduct association mining and cluster analysis
- Ability to run an analysis of survey data
- Ability to develop innovative design and research methods
- Ability to interpret and communicate results
- Ability to develop and conduct sophisticated data analyses
Career Opportunities in Nebraska for Data Scientists with Advanced Degrees
Data scientists can have a huge impact on everything from Nebraska’s biggest industries to its newest startups. The management consulting firm McKinsey and Company projects that data scientists could generate $300 billion in value each year for the healthcare system in the US. With the state’s largest employers including Children’s Hospital and Medical Center, Mutual of Omaha, and the University of Nebraska Medical Center, in a healthcare industry that generated over $9 billion in the state in 2019, that translates into a significant impact.
When browsing job vacancies for data scientists, students will notice how new this field is as companies list requirements that specify a master’s degree in a quantitative field, rather than specifically insisting on one in data science. Many of today’s candidates with graduate degrees did not have the option of obtaining a master’s in data science specifically since these programs are fairly new on the education scene.
But data science is becoming the preferred graduate degree focus, something that becomes clear when you look at the skyrocketing payrolls in the field. According to Robert Half’s 2020 Technology Salary Guide, data scientists in Omaha can make anywhere between $105,750 and $180,250 in the field today. That’s money that goes a long way in Nebraska!
The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment:
Predictive Analytics Supervisor with Kiewit in Omaha
- With one of the nation’s largest construction companies, this position involves using big data to solve problems that relate to engineering and construction
- Duties include using data analysis programs like R, Tableau, SQL, and SPSS, managing data analysis projects, and explaining technical concepts to non-technical audiences
- Preferred applicants hold an advanced degree in a quantitative field like mathematics, analytics, statistics, computer science, or economics
Health and Safety Professional with AECOM in Omaha
- With this professional and technical services firm, the incumbent in this position is expected to come from a background in environmental and health safety compliance
- Duties include applying scientific principles to develop solutions, collecting data, and applying technical principles and theories to analyze data and compare the results with state and federal regulations
- Preferred applicants hold at least a master’s degree in a relevant scientific discipline
Research Methodology Fellowship with Gallup in Lincoln
- With one of the world’s most respected pollsters, this position involves collecting, aggregating, and analyzing big data collected from throughout the world
- Duties include working with advanced research methodology and on advanced research projects with senior data scientists
- This fellowship provides funding for students who want to complete their master’s or PhD in the field of survey research methodology