The Land of Opportunity has both the industry and the educational and research backing to make it attractive to data scientists of every caliber and interest, with high-paying positions in diverse industries including finance and insurance, healthcare, biotech and pharmaceutical, retail, manufacturing and marketing, and even tax collection in the public sector.
Some interesting developments coming out of the nonprofit, Arkansas Foundation for Medical Care (AFMC), are coming at the perfect time as the healthcare industry is scrambling to cut costs while the pandemic cuts into the bottom line by forcing elective and non-essential procedures to be put on hold. Data scientists here develop and write data sampling frames, manipulate data, and produce visual representations that track client progress, giving healthcare providers a chance to remain solvent and keep their heads above water at a time when it’s needed most.
Working with massive data sets at research firms like Escalent in Little Rock, data scientists are responsible for quantifying the company’s research into statistical reports and creating easily minable data infrastructures.
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 2019 median salaries for data scientists ranged from $95,000-$167,000. With high earning potential and job stability in a field that will only continue to grow, earning a master’s degree in data science opens the doors to some of the best work the field has to offer in diverse industries across Arkansas.
Preparing for a Master’s Degree in Data Science in Arkansas
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 a relevant work history.
Undergraduate Degree and Master’s Prerequisite Courses
Minimum requirements candidates for data science master’s programs are expected to meet 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
Admissions departments will also consider an applicant’s prior work experience, GRE/GMAT exam scores, and knowledge of fundamental concepts. Each are important because coursework in a data science master’s degree will only 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 often 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++
- 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
Online Data Science Bootcamps to Prepare For Master’s Program Applications and Acquire Hands-On Skills
You’re probably getting the picture by now that getting a slot in a well-respected master’s degree program is a pretty competitive process. You are going to have to bring both skills and ambition to the table, along with a root-level knowledge that demonstrates you can hit the ground running in high-level data science courses.
One way to prepare yourself for all of this is by enrolling in a data science bootcamp. These short-term, intensive courses offer a firehose of essential analytics skills and techniques with a focus on practical, real-world implementations. That even extends to primarily relying on live datasets available from a variety of public and private sources, cutting your teeth on the same kinds of real data that you would see out in the workforce.
It’s all taught cohort-style, by experienced instructors who are experts in the use of the tools and techniques they are teaching. You typically engage in group projects to build a working portfolio that you can later use to demonstrate your skills to potential employers or admissions committees. It all happens in just a few weeks or months, and today you can find many excellent programs in Arkansas that are available online, 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
While there are a wide variety of bootcamps on offer in the United States today, aimed at all possible skill levels and many different specialties in the field, these college-affiliated bootcamps give you the assurance of a major, highly-respected educational institution standing behind the program. That means better career services, professional instructors, and vast data processing and management resources.
That particular set of programs are aimed at entry-level data scientists, so the entrance requirements are relatively low: a GED and having passed your 18th birthday can get you in the door. Other programs, more specialized or advanced, might require a bachelor’s or masters and years of experience in the field for admission.
But a ground-level introduction into the essentials of machine learning, statistical modeling, database programming, and visualization techniques will impress either employers or master’s program admissions committees. You’ll develop skills in:
- Advanced Excel use
- JavaScript programming and libraries like D3.js and Leaflet.js
- Social Media Mining
- SQL Databases
- Hadoop
The first data science bootcamps were all in-person and full-time, but an increasing number today are offered both online and in part-time formats that can accommodate working professionals. Almost all of them deliver some sort of career counseling service for graduates, which will help you build a resume and prepare for interviews with either master’s programs or future employers.
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 take a different approach to education, with a more self-directed, a la carte style. By their nature, you won’t have as much interaction with instructors or fellow students, although some faculty are usually available for questions. On the plus side, they can be self-paced, allowing you to work through them at your own speed, and also are available on every topic under the sun, so you can select exactly the subjects that you need a boost in, and avoid spinning your wheels studying things you are already familiar with.
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 fact that they make room for a normal work 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 program curriculum will cover the fundamentals of data science, while core coursework will include some variation 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 and statistical sampling
- Machine learning and artificial intelligence
- Experiments and causal inference
- Data research design and applications
- Data mining
Key Competencies and Objectives
Data science programs assess your progress toward becoming a competent data scientist in a number of ways. Although you may take different paths through the program, you’ll emerge with a common set of skills and capabilities revolving around 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 the job market landscape entirely, opportunities for data scientists are only increasing. Data scientists are needed to mine, interpret, and analyze data in all sectors.
Data Scientist at Okaya in Bentonville
Requirements:
- Master’s degree in a data science related field
- 5 years of experience in R, Python and SAS
Responsibilities:
- Implement analytical models on existing platforms
- Apply analytics to supply chain management
Data Engineer at Windstream Communications in Little Rock
Requirements:
- Master’s degree in a data science related field
- 2-4 years of professional experience as a data scientist
Responsibilities:
- 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
Requirements:
- Master’s degree in a data science related field
- At least 5 years of CRM and database marketing consulting
Responsibilities:
- 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