7 Data And Analytics Job Titles To Know

analyst jobsIT organizations looking to transition to enable digital business are frequently tasked with turning their data into value. You don’t need to look any farther than the 2016 InformationWeek Elite 100 to notice that most of the projects on the list included leveraging data in new ways.

It makes sense that professionals who can leverage data are in demand. This is true not only at tech companies, but across many industries, as financial companies, insurance companies, media companies, shipping companies, healthcare providers, entertainment companies, and others, all become data and software development companies.

Careers website Glassdoor’s Economic Research group recognized Data Scientist as the Best Job in America for 2016 based on a few different criteria, including median base salary and the number of US job openings in January when the report was released. In the post releasing these results, the organization noted several trends revealed by the list, including the fact that 10 of the 25 best jobs are technology jobs.

“A decade ago, these positions were mostly within companies like Google and Facebook,” the post said. “But today they’re diffusing throughout the economy in industries like banking, retail, consulting and government. Any organization with a mobile app, online payments, or digitized data that can be turned into business insights is hiring these positions right now.”

That means you don’t have to live in Silicon Valley, San Francisco, New York, or Boston to land a job in one of these fields.

“There has never been a better time to be a Quant,” is how Burtch Works puts it. Burtch Works is an executive recruitment firm specializing in data scientists, predictive analytics pros, and other data analytics professionals.

If you have worked in an IT organization, maybe you are considering a move over to the data side of the house as jobs like data scientist are identified as being in great demand and having high salaries. But not all data jobs are the same. There are data scientists, data engineers, data analysts, predictive analytics professionals, business intelligence professionals, and more.

While some of these jobs may have overlapping skills and responsibilities, they also have distinctions. InformationWeek looked at several titles and how those titles were defined by analysts, consultants, and recruiters. We compared actual job listings to break down the titles and skills needed. The following pages present our list of titles.

Data Scientist

Data scientist is the job title that’s been getting lots of attention over the last few years, after Glassdoor named it the best career for work/life balance. Salaries are also relatively high. But what does it mean to actually be a data scientist?

Burtch Works defines data scientists as those who “apply sophisticated quantitative and computer science skills to both structure and analyze massive unstructured data sets or continuously streaming data, with the intent to derive insights and prescribe action.” The executive recruiting firm says that the depth and breadth of these professionals’ coding skills distinguishes them from other predictive analytics pros, and allows them to exploit data regardless of the source, size, or format.

These data pros often have a master’s or a PhD in a quantitative discipline, such as applied mathematics or statistics, have expert knowledge of statistical and machine learning methods using tools such as R and SAS, according to Burtch Works. They are also usually proficient users of big data technologies such as Hadoop and Spark.

Advanced Analytics Professional

Advanced analytics professionals typically perform predictive analytics, prescriptive analytics, simulations, and other forms of advanced analysis. They differ from data scientists because they don’t work with exceptionally large data sets or with unstructured data, according to Burtch Works.

Data Analyst

Data analyst job listings run the gamut of responsibilities, from ensuring data quality and governance, to creating systems that enable business users to gain insights, to performing actual data analysis. But the skill sets are similar. Generally, these pros fit into the same category as advanced analytics and data scientist professionals, because they all can analyze data. However, data analysts may be considered more junior-level pros who are still generalists and can fit into several different roles within an organization.

Data Engineer

Data engineers work behind the scenes to make the jobs of data scientists and data analysts easier. These technology pros have deep knowledge of Hadoop and big data technologies such as MapReduce, Hive, and Pig, SQL technologies, NoSQL technologies, and data warehousing solutions. Their jobs are to build the plumbing — data pipelines that clean, aggregate, and organize data from different sources, and then load them into databases or data warehouses. Data engineers don’t analyze the data. Rather, they create the software infrastructure that keeps the data flowing and processing so that other professionals can analyze the data.

Business Analyst

Business analysts can perform tasks that are very similar to those performed by data analysts. However, business analysts typically have specialized knowledge of their business domain, and they apply that knowledge and analysis specifically to the operation of the business. For instance, they may use their analysis to recommend improvements to business processes.

Database Administrator

This professional is responsible for all things related to the operation, monitoring, and maintenance of databases — often SQL or other relational database management systems. Their tasks include installation, configuration, defining schemas, training users, and maintaining documentation. Database vendors including IBM, Microsoft, and Oracle often offer certifications specific to their own technologies.

Business Intelligence Professional

Business intelligence professionals are those adept at using OLAP tools, reports, and dashboards to look at historical trends in data sets. Business intelligence can include data visualization, and popular business intelligence platforms include Tableau, Qlik, and Microsoft Power BI.

Source www.informationweek.com