Louisianans know firsthand how important good information can be, having come through an event like Katrina, which represented a huge failure of data assessment, and having paid for it in lives. It’s one of the great examples of how even with data being readily available, without skilled analysts to process and pull insights from it, it means nothing.
Since then, data scientists have been hard at work not only developing better flood risk assessments for the low-lying properties around the state, but also coming up with innovative ways to model and visualize that information so that policymakers, municipal planners, civil engineers and residents alike can understand it.
Virtually all the credit for Flood Factor, a site developed by the First Street Foundation, goes to the data scientists on staff there. The tool allows people in New Orleans, outlying areas in the state, and virtually anywhere else in the country, to check flood risks on an address-by-address basis and assess both current and projected flooding risks for individual properties and wider areas.
Of course nonprofits and government agencies like the Army Corps of Engineers are not your only employment options as a data scientist in Louisiana. With a shortfall of some 150,000 skill-equipped data-scientists nationwide as found by LinkedIn in 2018, just about every industry is hurting for expertise in this field. From oil and gas to agriculture, every industry in the state is hungry for data scientists with the right skill set.
Preparing for a Master’s Degree in Data Science in Louisiana
With the demand for data scientists increasing, paychecks are skyrocketing as fast as job openings. Robert Half’s 2020 Technology Salary Guide found that data scientists in New Orleans with the right skills are getting starting offers of between $105,000 and $178,000. And those skills are something that come with the right level of education, so more and more professionals are pursuing a master’s degree to learn the complex skill sets that the world’s highest earning and most innovative companies are looking for in the data scientists they recruit.
Those programs aren’t always easy to get into, however. You’ll need strong preparation to get a spot.
Undergraduate Degree and Master’s Prerequisite Courses
That preparation starts with your undergraduate degree. 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 (waivers often granted with the right experience)
- Prior work experience
- Fundamental concepts
Preparing for Success on the GRE/GMAT Exams
Unless eligible for a waiver based on industry experience, applicants would typically have to score in the top 15% on the quantitative section of the GRE or GMAT to position themselves for admission to a master’s program 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
- Quadratic equations
- Algebraic expressions
- 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
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 committees will give top consideration to applicants who have demonstrated exceptional quantitative and analytical reasoning capabilities and strong communication skills throughout their work history. This typically includes:
- Programming proficiency in languages such as Java, C++, and Python
- Total relevant work experience (five years is preferred)
- Communication skills
- Database administration proficiency
Examples of qualifying work experience in Louisiana could include:
- Data analysis at CenturyLink
- Cyber Security at Entergy
- Data management at Albemarle
Online Data Science Bootcamps to Prepare You for a Master’s Program or Direct Entry into the Industry
Data science bootcamps are one option to build your skills and knowledge to the level that is expected of master’s program candidates. Although they offer a completely different type of experience than traditional degree programs, they do deliver a rapid, relatively inexpensive, hands-on education in data science that you can put toward either career-building or polishing your CV for a master’s admissions committee.
Bootcamps started out as quick, intensive, in-person introductions to the field designed to get people up to speed with unfamiliar concepts and techniques without years of formal study, and were usually offered by small private for-profit companies. But the concept has evolved to offer a range of different education levels, from the introductory to the very advanced. They have also moved online and are now frequently offered by well known colleges and universities. You’ll study all the cutting-edge technologies and topics critical to the field, with curriculum delivered by experienced instructors:
- Basic HTML/CSS tools for data presentation
- Advanced statistics
- R, JavaScript, and Python programming
- SQL and SQL databases
- Big Data analysis and Hadoop
You’ll take it all in as part of a larger cohort, working on specific projects that get you hands-on with real world data, just as you would be doing out in the workforce.
Although you may be using a bootcamp as preparation for further studies at the master’s level, many of your cohort will be heading right into the workforce. Bootcamps typically offer a wide range of career services to aid in that process, from arranging interviews and helping you develop a portfolio to demonstrate your skills, to holding demo days for potential employers to review your work. In either case, you get an edge on the competition after a stint in a data science bootcamp.
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 come up short in one or more of these admission standards should 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 to students who have been accepted into the program but who might have some unmet education requirements they need to complete 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
You’re likely to be offered the option of taking bridge courses if you need to brush-up on some core skills, but are otherwise a valuable master’s candidate. You’ll only have this option if the school decides to offer it to you, so if you are shaky in your abilities, it’s not exactly Plan A.
MOOCs – Massive Open Online Courses – Something that you can do on your own before ever applying for entry is to boost your skills through a MOOC. Massive open online courses offer you a selection of different subjects and styles, and can be completed on your own timeline and used to boost your skills without relying on formal coursework. These courses are offered in a number of subjects and consist of diverse online learning formats such as video lectures, interactive forums, and problem sets.
Earning a Master’s Degree in Data Science in Louisiana
Data science master’s programs consist of curricular coursework and an immersion experience, which allows students to apply their knowledge through real-world problem-solving. Degree and certificate program titles could include:
- 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
Aspiring data scientists in the state often pursue their degree online through an accredited program. Typically consisting of both live classes and self-paced coursework, online master’s programs in data science allow students to earn degrees like 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
- File organization and database management
- Experiments and causal inference
- Information visualization
- Machine learning and artificial intelligence
- Ethics and law for data science
- Experimental statistics
- Applied regression and time series analysis
- Network and data security
- Data storage and retrieval
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 applications, giving them a chance to demonstrate their talents before entering the professional realm.
Key Competencies and Objectives
Data science master’s graduates are equipped with all the in-demand skills. 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
- 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 Louisiana’s business community is increasingly relying on the insights derived from talented data scientists, the state has become a promising 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.
And they know what they’re talking about. Headquartered in Monroe, the telecom giant is perhaps the highest profile big data employer in Louisiana. The corporate powerhouse offers data science services to a variety of organizations, focused on:
- Data Integration
- Predictive Analytics
- Data Visualization
- Business Intelligence
- Model Risk Assessment
- Data Governance
But CenturyLink isn’t the only big player in town. The following job listings 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 consists 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 consists 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