The terms "data scientist" and "data engineer" are sometimes used interchangeably and involve similar skill sets. However, the roles of data scientists and data engineers are appreciably different.
The main job for both data scientists and engineers is to take large and small quantities of data and create new ways to analyze and utilize that data. Data scientists use their expertise (usually in the natural or social sciences), along with mathematics, statistics, and computer science to analyze data and provide solutions for critical issues. Data engineers employ similar skills with the purpose of gathering, organizing, and storing data. In other words, data engineers provide clean, organized, accessible data to data scientists who analyze it to solve problems and create new technologies based on their findings.
Data scientists and engineers typically work with computers in office settings and are often integrated into teams with other data scientists and engineers. These teams may also include business architects, research scientists, information technology (IT) staff, and junior analysts, all of whom are supervised by a senior project manager or other middle management position. There are many areas in which data scientists and engineers are employed. Some of these include clinical data, cloud computing, information retrieval and access, signal processing, marketing, and data security. Data scientists and engineers can be found in both corporate and academic settings.
Both data scientist and data engineer positions require at minimum a bachelor's degree in computer science, applied math, information science, or a related discipline. Some industries require additional expertise in fields such as astronomy, biology, or economics. Employers often request higher-level degrees but many will accept several years of related experience in lieu of a master's or Ph.D. Data scientists and engineers must be comfortable with programming languages such as Java Script, C++, Perl, and Python; the ability to use databases and SQL; and a robust understanding of statistical analysis and modeling, along with theories and tools of data analysis.
Data Scientist / Engineer Tasks
Perform and interpret data studies and product experiments concerning new data sources or new uses for existing data sources.
Develop prototypes, proof of concepts, algorithms, predictive models, and custom analysis.
Design and build new data set processes for modeling, data mining, and production purposes.
Determine new ways to improve data and search quality, and predictive capabilities.