Filed under: News
Jan 16 2014, 1:36pm CST | by Forbes
Data Science is gaining traction in the industry, as analytics, data collection, sensors, and Big Data become a more regular part of our online existence. O’Reilly Media, Inc. recently released a survey that it had conducted during 2012 and 2013 on its audience for its Strata Conference focused on this topic in advance of its event on February 11-13, in Santa Clara.
[As a note for the data scientists reading this, the two surveys were conducted only about 4 months apart according to the O’Reilly team, which should reduce the variations due to the multiple collection intervals over time. n=583, 387 from 2012 and 136 from 2013. Per one of the authors, John King, "while there were some differences in basic demographics between the conferences' subsamples (e.g., startups had a greater presence in the Santa Clara subsample), the main patterns we present in the report are valid for each subsample. " ]
O’Reilly’s conferences typically draw a more technical audience, particularly from the IT and hi-tech fields, so it should not be a surprise that a significant portion of the participants come from the software, application development, and IT solutions industries. In addition, Tech Lead was the most common job role (52%), although “almost all reported that some part of their role included technical duties (i.e., 10–20% of their responsibilities included data analysis or software development).”
The largest segments were in the age ranges 30 – 39 (33%) and 40 – 49 (29%), with about 40% of respondents from the Western US, particularly from the technophilic states of California, Colorado and Washington. The salaries ranged from $100,000, rising with the degree of familiarity with the tools of the trade up towards $130,000 with 15+ common data science tools. Median salary for the US respondents was $110,000.
In a quick comparison on employee self-reported salary and job site, glassdoor.com, for the job title “Data Scientist”, median salary reported was $117,500, across nearly 300 jobs in the US. This follows the O’Reilly survey data well. Per the earlier statement, the role of data analysis can fall into many job roles rather than requiring a strictly specialized Data Scientist title, which makes it a little more difficult to accurately map through job sites.
Most interesting of the survey data is the specific clustering of technical skills and the correlation to pay ranges. Figure 1 describes the two main clusters of tools and development experience that they label Hadoop tools and SQL/Excel tools. The former includes a number of tools from the open source pantheon such as distributed development (Apache Hadoop, Hive), programming languages (R, Java and Python), open databases (MongoDB, Hbase), and social graph processing tools (unspecified). While the latter includes more commercial applications such as SQL databases (Microsoft, Oracle), spreadsheets (Microsoft Excel), analytics (SAS), visualization (Tableau, Netezza, Business Objects), and programming languages (Visual Basic, C#). Per the report,
Using more tools from the Hadoop cluster correlates positively with salary, while using more tools from the SQL/Excel cluster correlates (slightly) negatively with salary.
Alistair Croll, chair of O’Reilly’s Strata conference shared some views of what to expect in this field. First, he notes that the harsh light of data changes how we understand the world, citing:
As Mr. Croll indicates there are consequences of looking at data. Our foray into Big Data is bringing to light the ongoing challenges we face of living a global existence while still bounded by territories and nations: our various views on privacy and identity; the economic upheaval brought about, as Clay Shirky describes in Cognitive Surplus, from an economy of abundance rather than scarcity; or the challenge to traditional hierarchies as people at the edge have better situational awareness than strategists at the core.
Source: The Edge Singapore
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