An Employer’s Guide to Data Science Credentials

It’s no secret that data scientists are in demand in just about every modern industry. The reason for the high demand is an obvious one. Across the globe, 2.5 quintillion bytes of data are generated every day, and we’re just beginning to understand the countless ways that it can be put to use. It’s also a fact that more than 90% of all of the world’s data has been created since 2014. That is a scale and speed that almost nobody expected and that the employment market wasn’t prepared to accommodate.

Fortunately for businesses, the education industry is starting to catch up with demand and is producing a whole new generation of data scientists to take on the challenge of finding new and innovative ways to deal with the torrent of available data. For businesses that are just beginning to build out their data and analytics teams, it’s crucial to understand the different levels of educational training that are currently available in the field so that they can determine what to require of prospective hires. Here’s a guide to the kinds of data science degrees that candidates may hold and which positions they will excel at.

Bachelors in Data Science

As is the case in most other fields, a bachelor’s degree in data science trains the holder in the basic concepts, skills, and competencies required for many lower level data science positions. They will be well versed in statistics and mathematics as they pertain to analytics. They will also possess a working knowledge of data visualization, data structure, and algorithmic functions.

With those skills, a candidate with a bachelors in data science will be well qualified for positions such as:

• Business Intelligence Analyst – Performs data collection and analysis to improve business efficiency and create policy based on insights gleaned from operational data.
• Data Visualization – Supports the creation of BI reports from existing business data sources and works with management to provide easily digestible data formats for decision makers.
• Market Researcher – Compiles and analyzes sales and industry data to identify business strengths and weaknesses, and to provide guidance for expansion or revenue-generation.

Master’s in Data Science

A master’s degree in data science is the most commonly attained level of education in today’s market, with 64% of data scientists holding such a degree as of 2017. Their popularity has grown in recent years due to the availability of online master of data science programs from well-known schools like James Cook University. Holders of a master’s degree in data science process high-level skills in programming, statistical analysis, and mathematics.

They’re well suited to a variety of data science positions, most notably:

• Statistician – Provides actionable analysis based on existing business data to derive business insights and solve real-world operational issues and support business goals and initiatives.
• Algorithm Development – Skilled in data mining and machine learning applications used to create usable BI reports for managers and executives.
• Data Engineer – An IT-focused manager and operator of data collection and warehousing applications, overseeing data mining, cleaning, and quality standards.

Doctorate in Data Science

In the early days of big data adoption, professionals holding a PhD in data science ruled the industry. They were primarily tasked with building the systems, procedures, and methods that form the basis of modern data science. Today, as the data tools available to businesses have become mainstream and accessible, the demand for the advanced skills a PhD confers have waned. Still, for customized analytics and big data solutions, there is no substitute for these valuable professionals. They possess the knowledge required to build mathematical models and applications from the ground up, and still form the core of every credible big data operation.

Holders of a PhD in data science are required to fill positions like:

• Data Scientist – Utilizes advanced computer science skills to develop predictive modeling applications. Gathers, cleans, and analyzes complex data from disparate sources of structured and unstructured data.
• Business Solutions Scientist – Builds business data solutions based on probability theory, statistics, and machine learning systems to provide high-level business intelligence.
• Enterprise Analytics Manager – Creates and manages all aspects of business analytics operations, designing solutions and working with staff to create customized data solutions for specific business needs.

An Unquenchable Need

As we progress further into the 21st century, data scientists will no doubt become the true indispensable members of every business. They are on the leading edge of a revolution in the way companies everywhere conduct business and gain competitive advantage. In the coming years, advances in the development of IoT devices and AI-powered products will only add to the quantity, quality, and velocity of data flowing into and through industries both large and small.

The nature of the current market demands that employers find and hire data science professionals with the right mix of skills to meet their current and future needs. The degrees and positions listed above should provide an excellent guideline to accomplish that task. Those that don’t risk being left behind the pack in the race for data supremacy.

To learn more about how data science is changing economies, read Predictive Analytics Could Offer Intelligence-Led Economic Progress.

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