Online Master's in Data Science for Jobs in Nebraska

The big data revolution has brought data scientists to the forefront of demand in key Nebraska industries including finance, healthcare, transportation, military, and local government. Smaller tech startups who are also locating in Lincoln – “Silicon Prairie” – like Bulu Box and Opendorse, are also helping to drive the demand for data scientists in Nebraska.

Doing everything from computer model development to finding new ways to obtain information, data scientists work with the state’s smallest companies and largest corporations. First Data Corporation, the nation’s largest payments industry company that was originally headquartered 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.

Transportation is an example of another industry that can benefit from data scientists. With $4.2 billion generated by rail transportation in 2013, Nebraska is home to the largest railroad classification yard in the world, Bailey Yard in North Platte. Data scientists can 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 this freshly established field are quickly becoming standardized, with companies recognizing the skills demonstrated by a master’s degree in data science as being foundational.

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 degree programs 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

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:

  • Statistics
  • Calculus I and II
  • Quantitative methods
  • Linear algebra
  • programming languages like JAVA and Python

Relevant Personal and Work Experience

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, hacking, math, statistics, data mining, or database administration
  • Demonstration of analytical reasoning ability
  • 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 15th percentile of the GRE/GMAT. 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.

The Graduate Record Exam (GRE) revised general test’s quantitative reasoning section 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.

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 of a diverse set of skills. To supplement an applicant’s bachelor’s education, data science graduate programs may require newly admitted students to complete a bridge program in an area their academic record lacks. Bridge programs are normal university undergraduate courses or a series of courses in a specific subject. 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.

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. While there are currently no in-state master’s programs specifically in data science, students can find some relevant options:

  • Undergraduate minor in informatics – available in Lincoln
  • Undergraduate major in sociology with a focus in data science – available in Lincoln
  • Bachelor’s of Science (BS) in Mathematics with a concentration in data science – available in Omaha
  • Master’s of Science (MS) in Mathematics with a concentration in data science – available in Omaha

Nebraska residents also have the option of getting the full advantages of a master’s degree in data science online. Colleges and universities offering their data science graduate programs online also enroll students in a variety of accommodating schedules:

  • 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:

  • Statistical sampling
  • Information visualization
  • Ethics and law for data science
  • Machine learning and artificial intelligence
  • Data mining
  • Experiments and casual inference
  • Quantifying materials
  • Network and data security
  • Macro and micro data scaling
  • Data storage and retrieval
  • Advanced managerial economics
  • File organization and database management
  • Applied regression and time series analysis
  • Data research design and applications
  • Visualization of data
  • Experimental statistics
  • Immersion

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. 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:

  • Familiarity with programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
  • Ability to work in teams to achieve specific goals
  • Familiarity with hash algorithms, cyphers, and secure communications protocols
  • 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
  • Ability to conduct database queries

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 CHI Health, Methodist Health Center, the Nebraska Medical Center, and the University of Nebraska Medical Center, in a healthcare industry that generated $6.89 billion in 2013, 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.” Many of today’s candidates with graduate degrees did not have the option of obtaining a master’s degree in data science since graduate programs specific to the field were not yet developed.

(The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment. These examples were taken from a survey of job vacancy announcements for data scientists in Nebraska, completed in February 2016):

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 Ph.D in the field of survey research methodology

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