Online Master's in Data Science for Jobs in Arkansas

In Arkansas, data scientists with master’s degrees have the opportunity to work in many different sectors. McKinsey and Company reported that by 2009, “nearly all sectors in the US economy had at least an average of 200 terabytes of stored data,” allowing data scientists many opportunities to manipulate and quantify data within those sectors. Some of those industries include finance and insurance, healthcare, biotech and pharmaceutical, retail, manufacturing and marketing, as well as HR and tax revenue collection in the public sector.

At the Arkansas Foundation for Medical Care (AFMC), data scientists develop and write data sampling frames, manipulate data, and produce graphs, charts and visual representations that track client progress and keep a dynamic record of the foundation’s health services. Arkansas’s data scientists may also find work in research firms like Cognent Research in Little Rock where they would be responsible for quantifying the company’s research into statistical reports, creating data mining infrastructures, and working with extremely large data sets.

Regardless of sector, data scientists in Arkansas who have earned master’s degrees have the opportunity to earn a higher salary. According to executive recruiting firm Burtch Works, in 2014 median salaries for data scientists ranged from $80,000-$155,500. With high earning potential and job stability in an industry that will only continue to grow, earning a master’s degree in data science opens the doors to opportunities in Arkansas’s diverse industries.

Preparing for a Master’s Degree in Data Science in Arkansas

Master’s-prepared data scientists have the opportunity to seek high paying positions in many different sectors. Because of the diverse skill set necessary to obtain these jobs, data science master’s programs set highly selective admissions requirements. Candidates must demonstrate fundamental knowledge of data science concepts along with excellent educational and work history.

Undergraduate Degree and Master’s Prerequisite Courses

Candidates for data science master’s programs must meet certain minimum requirements, which often include:

  • Bachelor’s degree in a related field such as statistics, computer science, engineering, or applied math
  • Minimum 3.0 GPA in undergraduate coursework

Mandatory prerequisite courses for data science students include the following:

  • Statistics
  • Calculus
  • Linear algebra
  • Programming languages, especially JAVA and Python

Admission departments will also consider the applicant’s prior work experience, GRE/GMAT exam scores, and knowledge of fundamental concepts.

In data science master’s programs, coursework will build upon an established set of skills. In order to be accepted into the program, candidates will need to be comfortable and familiar with the following areas:

  • Data structures
  • Algorithms and analysis of algorithms
  • Linear algebra

Preparing to Perform Well on the Quantitative Sections of the GRE/GMAT Exams

Master’s program applicants are expected to score in the top 15 percent of the GRE or GMAT’s quantitative section. Universities also place emphasis on the verbal and writing sections of the exams, expecting applicants to be excellent communicators.

The GRE’s quantitative section will evaluate the candidate’s knowledge of the following disciplines:

  • Data analysis, including statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
  • Arithmetic, including integers, factorization, exponents, and roots
  • Algebraic topics, including algebraic expressions, functions, and linear equations
  • Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem

Students may prepare for the GRE by reviewing sample practice questions and two free practice tests available through the official GRE website. For additional preparation, students may schedule a free GRE practice exam through The Princeton Review or Veritas Prep.

The GMAT’s quantitative section will evaluate:

  • Problem solving
  • Data efficiency

Students may prepare for the GMAT exam by taking full-length practice exams hosted by The Princeton Review and by Veritas Prep.

Prior Work Experience and Related Skills

Master’s programs require 5-7 years of prior work experience in a data science related field. In addition to employment experience, admissions offices expect applicants to have proficiency in the following areas:

  • Programming languages, especially JAVA, Python, and C++
  • Coding
  • Hacking
  • Data Mining
  • Database Administration

In Arkansas, applicants may acquire work experience through entry-level positions that may include:

  • Entry-level engineering technician at Gates Corporation in Siloam Spring setting up, maintaining, and utilizing data acquisition systems
  • Support analyst with the Arkansas Department of Human Services in Little Rock, researching and analyzing data, developing and revising policies based on research, and submitting report findings
  • Research analyst at Arkansas State University in Jonesboro, analyzing data sets and interpreting them for reports
  • Data scientist at local nonprofits
  • Data programmer in local government offices

Bridge Programs and Massive Open Online Course (MOOC) Options for Applicants Who Do Not Meet Admission Criteria

Data science master’s programs require students to possess a unique skill set as well as prior work and educational history in related skills. Because bachelor’s prepared candidates seeking admission to a master’s program may not meet each requirement, most universities offer bridge programs to allow graduate students an opportunity to gain proficiency as needed in the fundamental disciplines of data science.

Generally, two types of bridge programs are made available:

  • Fundamental (including linear algebra, algorithms and analysis of algorithms, and data structures)
  • Programming (including languages such as Python, JAVA, C++)

Massive Open Online Courses include non-degree related supplementary education tools which offer aspiring master’s program students another avenue to supplement their education. MOOCs offer online problem modules, filmed lectures, and the opportunity to seek instruction from professors, teaching assistants, and other students.

Earning a Master’s Degree in Data Science in Arkansas

Arkansas is home to a handful of traditional in-state, on-campus master’s programs in data science. However, more and more, working professionals are choosing to enroll in accredited online programs, citing benefits such as flexibility and the ability to complement a professional schedule. Online programs offer full-time, part-time, and accelerated options.

Most data science programs require an immersion experience near the end of the program, a hands on project collaboration among master’s students. The immersion experience will require students to visit campus.

Full-time programs are typically completed in 18 months, part-time programs can be completed in 32 months, and accelerated options can be completed in as little as 12 months.

Data scientist students may choose from several different programs:

  • Master of Science in Data Science
  • Master of Information and Data Science
  • Graduate Certificate in Data Science
  • Data Mining Graduate Certificate
  • Data Science Graduate Certificate

Curriculum and Core Coursework

Master’s programs in data science will require courses covering the fundamental of data science. Core coursework will include a combination of the following topics:

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

Key Competencies and Objectives

Data science programs will prepare students for the challenges of working in the field. Programs seek to build proficiency in the following areas:

  • Statistical sampling
  • Data collection and analysis
  • Research design
  • Data mining and machine learning
  • Communication and visualization
  • Ethics, privacy, and relevant law
  • Database management and file organization
  • Data and network security
  • Data cleansing
  • Programming languages such as Python, GitHub, and SAS
  • Database queries

Career Opportunities for Data Scientists in Arkansas with Advanced Degrees

As a growing reliance on technology sweeps across businesses and changes company landscapes, job opportunities for data scientists increase throughout the state. Data scientists are needed to mine, interpret, and analyze data in all sectors.

Data Scientist at Okaya Infocom IT Consulting Firm in Bentonville, AR


  • Master’s degree in a data science related field
  • 5 years of experience in R, Python and SAS


  • Implement analytical models on existing platforms
  • Apply analytics to supply chain management

Data Engineer at Windstream Communications in Little Rock, AR


  • Master’s degree in a data science related field
  • 2-4 years of professional experience as a data scientist


  • Using data mining and cluster analysis, determine new opportunities for statistical analysis applications
  • Build programs for running statistical tests and predictive models
  • Provide guidance and direction to other team members

Senior Data Scientist at Cyber Coders, in Little Rock AR


  • Master’s degree in a data science related field
  • At least 5 years of CRM and database marketing consulting


  • Use data mining to determine relevant changes to company systems
  • Manage and maintain data systems while supervising data science team
  • Lead analysis of big data and create deliverables for clients

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