Data Scientist / Engineer Salary
Job Description for Data Scientist / Engineer
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.Read More...
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
- 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.
- 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.
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Popular Skills for Data Scientist / Engineer
Survey participants wield an impressively varied skill set on the job. Most notably, skills in Apache Spark, Scala, Hadoop, and Data Mining / Data Warehouse are correlated to pay that is above average, with boosts between 9 percent and 19 percent. Skills that seem to negatively impact pay include Microsoft SQL Server, Data Modeling, and Apache Hadoop. For most people, competency in Data Analysis indicates knowledge of Statistical Analysis and Hadoop.
Pay by Experience Level for Data Scientist / Engineer
Median of all compensation (including tips, bonus, and overtime) by years of experience.
Experience seems to be a major factor in determining the incomes of Data Scientists. Whereas the median salary for inexperienced employees is approximately $86K, incomes in the five-to-10 year group are significantly higher, averaging to the comfortable six-figure sum of $108K. The average pay reported by folks with 10 to 20 years of experience is around $120K. Old hands who claim more than two decades on the job enjoy average earnings of $155K.
Pay Difference by Location
Home to some of the best pay for Data Scientists, Mountain View offers exceptional salaries, 43 percent above the national average. Data Scientists can also look forward to large paychecks in cities like New York (+36 percent), San Francisco (+31 percent), Palo Alto (+27 percent), and Seattle (+18 percent). Location is a huge contributor to overall pay, with Data Scientists in Dallas earning a whopping 22 percent below the national average. Washington and Atlanta are a couple other places where companies are known to pay below the median — salaries are 21 percent lower and 14 percent lower, respectively.
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Key Stats for Data Scientist / Engineer
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