Online Master's in Data Science for Jobs in Louisiana

Louisiana’s economic development efforts since 2008 have significantly bolstered business in the state, leading to some $28 billion in new capital investment, according to the Louisiana Department of Economic Development. As companies continue to turn to data scientists to develop innovative strategies and solutions, this massive business boom is increasing the number of employment opportunities for qualified data scientists in the state.

At the center of Louisiana’s recent economic surge is the state’s software development industry. According to the Louisiana Department of Economic Development, the state provides the nation’s “strongest, most comprehensive incentive” for software development, financially backing both the efforts of both higher education institutions and innovative companies. This investment will undoubtedly benefit the future of data science in the state, as software development companies will continue to employ qualified talent to remain at the forefront of cutting-edge technologies.

Perhaps the highest profile employer of data scientists in Louisiana is telecommunications company CenturyLink, headquartered in Monroe. The corporate powerhouse offers data science services to a variety of organizations, focusing on the following:

  • Data Integration
  • Predictive Analytics
  • Data Visualization
  • Business Intelligence
  • Model Risk Assessment
  • Data Governance

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

With data scientists becoming increasingly demand, more state professionals are pursuing a master’s degree in data science to learn the complex skill sets sought after by the world’s highest earning and most innovative companies.

Undergraduate Degree and Master’s Prerequisite Courses

Master’s programs in data science typically expect students to meet the following undergraduate profile:

  • Applicants must possess a bachelor’s degree in a field such as computer science, engineering, applied math, or statistics
  • Applicants must earn a minimum of a 3.0 GPA during undergraduate studies
  • Applicants must complete prerequisite courses in the following areas:
    • Statistics
    • Programming
    • Calculus I & II
    • Linear algebra

Beyond these core admission standards, programs consider applicant criteria in the following areas:

  • GRE and/or GMAT exams
  • Prior work experience
  • Fundamental concepts

Preparing for Success on the GRE/GMAT Exams

Typically, students would have to score in the top 15% on the quantitative section of the GRE or GMAT to position themselves for admission to master’s programs in data science. Schools may also evaluate applicants’ communication skills through the Verbal and Writing sections of these exams.

GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:

  • Algebraic topics such as:
    • Linear equations
    • Graphing
    • Quadratic equations
    • Algebraic expressions
    • Functions
  • Arithmetic topics such as:
    • Integers
    • Roots
    • Factorization
    • Exponents
  • Geometry topics such as:
    • The properties of triangles, quadrilaterals, circles, and polygons
    • The Pythagorean theorem
  • Data analysis topics such as:
    • Statistics
    • Standard deviation
    • Probabilities
    • Interquartile range
    • Permutations
    • Venn diagrams
    • Graphs

To prepare for the GRE, students may access practice exams by signing up with the Princeton Review or downloading a free program through Educational Testing Service (ETS).

GMAT – The quantitative section of the Graduate Management Admissions Test (GMAT) consists of 37 questions designed to test students’ data analytics skills, particularly in problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through Veritas Prep and the Princeton Review.

Relevant Personal and Work Experience for Admissions

Admissions programs may give top consideration to applicants who have demonstrated exceptional quantitative and analytical reasoning abilities and strong communications skills through their professional work. Among the professional skill sets considered by these programs:

  • Programming proficiency in languages such as JAVA, C++, and Python
  • Data mining ability
  • Coding skills
  • Total relevant work experience (five years is preferred)
  • Hacking skills
  • Communication skills
  • Database administration proficiency

Examples of potentially qualifying work experience in Louisiana could include:

  • Data analysis at CenturyLink
  • Cyber Security at Entergy
  • Data management at Albemarle

Bridge Courses and Massive Open Online Course (MOOC) Options for Applicants that Need to Fill Gaps in Knowledge

Master’s in data science programs look for students who meet a wide array of qualifications. Students who lack one or more of these admission standards would enroll in bridge programs or massive open online courses (MOOCs) to fill their gaps in knowledge before beginning graduate studies.

Bridge Programs – A number of graduate schools offer bridge programs which allow prospective data science students to earn their outstanding education qualifications before beginning master’s-level coursework. These programs are typically offered in the following areas:

  • Fundamentals – These programs offer courses in linear algebra, algorithms and analysis of algorithms, and data structures
  • Programming – These programs offer courses in the programming languages necessary to begin graduate studies

MOOCs – Massive Open Online Courses – Students may also independently pursue massive open online courses before applying to master’s programs. These courses are offered in a number of subjects and consist of diverse online learning formats such as filmed lectures, interactive forums, and problem sets.

Earning a Master’s Degree in Data Science in Louisiana

Master’s in data science programs consist of curricular coursework and an immersion experience, which allows students to apply their knowledge through real-world data application. By completing these programs, students can earn credentials such as:

  • Data Science Certificate
  • Online Certificate in Data Science
  • Master of Information and Data Science (MIDS)
  • Data Mining and Applications Graduate Certificate
  • Master of Science in Data Science (MSDS)
  • Graduate Certificate in Data Science
  • Master of Science (MS) in Data Science

Programs may offer several different learning formats to meet students’ needs:

  • Full-time: Students may earn their degree in 18 months
  • Accelerated: Students can earn their degree in as little as 12 months
  • Part-time: Students typically earn their degree in 30-32 months

As of 2016, there are no campus-based master’s programs in data science in Louisiana. As a result, aspiring data scientists in the state often pursue their degree online through an accredited program. Typically consisting of both live courses and self-paced coursework, online master’s programs in data science allow students to earn degrees such as the Master of Science in Data Science (MSDS) or the Master of Information and Data Science (MIDS).

Core Curriculum and Immersion

Master’s programs in data science offer courses covering a wide range of skill sets that prepare students for the professional realm. Examples of these courses include:

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

In addition to these courses, master’s programs in data science require students to complete an immersion experience, which typically takes place in the final semester. Through these experiences, students collaborate with their classmates and professors on a project designed to simulate real-world data application, giving them a chance to demonstrate their talents before entering the professional realm.

Key Competencies and Objectives

Graduates of master’s in data science programs are equipped with a number of in-demand skill sets as they enter the professional realm. Most programs prepare students in the following core competencies:

  • Familiarity with hash algorithms, cyphers, and secure communications protocols
  • Working within a team setting
  • Conducting database queries
  • Using programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
  • Developing and conducting sophisticated data analyses
  • Survey data analysis
  • Conducting association mining and cluster analysis
  • Interpreting and communicating results
  • Developing innovative design and research methods

Career Opportunities in Louisiana for Data Scientists with Advanced Degrees

As businesses are increasingly relying on the insights derived from talented data scientists, Louisiana’s dedication to economic growth makes the state a promising future location for master’s-prepared professionals. In fact, CenturyLink states that the big data market is expected top $84 billion in 2026, which would represent a 17% annual compound growth rate.

The following job listings for data scientists in Louisiana were sampled in March 2016. They are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment.

Jr-Mid Data Scientist at CGI in Lafayette – The role would consist of duties including, but not limited to:

  • Leading Agile Scrum daily stand-ups
  • Developing and reviewing data architecture and statistical models
  • Troubleshooting technical issues
  • Leading technical design

Senior Data Scientist at CyberCoders (Remote) – The role would consist of duties including, but not limited to:

  • Defining and developing algorithms
  • Collaborating with the company’s production team and contributing to defining the logic of the production based on data stream integrity
  • Performing advanced and specialized data analyses

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