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(This article was first published on <strong><a href="http://r4stats.com/2017/03/13/jobs-for-data-science-up-7-fold-for-statistician-down-by-half/"> R – r4stats.com</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>The Bureau of Labor Statistics <a target="_blank" rel="nofollow" href="https://www.bls.gov/ooh/mobile/fastest-growing.htm">projects</a> that jobs for statisticians will grow by 34% between 2014 and 2024. However, according to the nation’s <a target="_blank" rel="nofollow" href="https://www.indeed.com/">largest job web site</a>, the number of companies looking for “statisticians” is actually in sharp decline. Those jobs are likely being replaced by postings for “data scientists.”</p>
<p>I regularly monitor the <a target="_blank" rel="nofollow" href="http://bit.ly/statpop">Popularity of Data Science Software</a>, and as an offshoot of that project, I collected data that helps us understand how the term “data science” is defined. I began by finding jobs that required expertise in software used for data science such as R or SPSS. I then examined the tasks that the jobs entailed, such as “analyze data,” and looked up jobs based only on one task at a time. I switched back and forth between searching for software and for the terms used to describe the jobs, until I had a comprehensive list of both.  In the end, I had searched for over 50 software packages and over 40 descriptive terms or tasks. I had also skimmed thousands of job advertisements. (Additional details are <a target="_blank" rel="nofollow" href="http://r4stats.com/articles/how-to-search-for-data-science-jobs/">here</a>).</p>
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<table width="392">
<tbody>
<tr>
<td width="159"><strong>Search Terms</strong></td>
<td width="88"><strong>2/26/2017</strong></td>
<td width="81"><strong>2/17/2014</strong></td>
<td width="64"><strong>Ratio</strong></td>
</tr>
<tr>
<td>Big Data</td>
<td>20,646</td>
<td>           10,378</td>
<td>1.99</td>
</tr>
<tr>
<td>Data analytics</td>
<td>15,774</td>
<td>             6,209</td>
<td>2.54</td>
</tr>
<tr>
<td>Machine learning</td>
<td>12,499</td>
<td>             3,658</td>
<td>3.42</td>
</tr>
<tr>
<td>Statistical analysis</td>
<td>11,397</td>
<td>             9,719</td>
<td>1.17</td>
</tr>
<tr>
<td>Data mining</td>
<td>  9,757</td>
<td>             7,776</td>
<td>1.25</td>
</tr>
<tr>
<td>Data Science</td>
<td>6,873</td>
<td>                 973</td>
<td><strong>7.06</strong></td>
</tr>
<tr>
<td>Quantitative analysis</td>
<td>4,095</td>
<td>             3,365</td>
<td>1.22</td>
</tr>
<tr>
<td>Business analytics</td>
<td> 4,043</td>
<td>             2,867</td>
<td>1.41</td>
</tr>
<tr>
<td>Advanced Analytics</td>
<td>3,479</td>
<td>             1,497</td>
<td>2.32</td>
</tr>
<tr>
<td>Data Scientist</td>
<td>3,272</td>
<td>                974</td>
<td><strong>3.36</strong></td>
</tr>
<tr>
<td>Statistical software</td>
<td>2,835</td>
<td>             2,102</td>
<td>1.35</td>
</tr>
<tr>
<td>Predictive analytics</td>
<td>                2,411</td>
<td>             1,497</td>
<td>1.61</td>
</tr>
<tr>
<td>Artificial intelligence</td>
<td> 2,404</td>
<td>                794</td>
<td><strong>3.03</strong></td>
</tr>
<tr>
<td>Predictive modeling</td>
<td>2,264</td>
<td>             1,804</td>
<td>1.25</td>
</tr>
<tr>
<td>Statistical modeling</td>
<td>2,040</td>
<td>             1,462</td>
<td>1.40</td>
</tr>
<tr>
<td>Quantitative research</td>
<td>                1,837</td>
<td>             1,380</td>
<td>1.33</td>
</tr>
<tr>
<td>Research analyst</td>
<td>                1,756</td>
<td>             1,722</td>
<td>1.02</td>
</tr>
<tr>
<td>Statistical tools</td>
<td>                1,414</td>
<td>             1,121</td>
<td>1.26</td>
</tr>
<tr>
<td>Statistician</td>
<td>904</td>
<td>             1,711</td>
<td><strong><span>0.53</span></strong></td>
</tr>
<tr>
<td>Statistical packages</td>
<td>                   784</td>
<td>                559</td>
<td>1.40</td>
</tr>
<tr>
<td>Survey research</td>
<td>440</td>
<td>                559</td>
<td>0.79</td>
</tr>
<tr>
<td>Quantitative modeling</td>
<td>                   352</td>
<td>                 322</td>
<td>1.09</td>
</tr>
<tr>
<td>Statistical research</td>
<td>208</td>
<td>                 174</td>
<td>1.20</td>
</tr>
<tr>
<td>Statistical computing</td>
<td>                   153</td>
<td>                 108</td>
<td>1.42</td>
</tr>
<tr>
<td>Research computing</td>
<td>                   133</td>
<td>                   97</td>
<td>1.37</td>
</tr>
<tr>
<td>Statistical analyst</td>
<td>                   125</td>
<td>                 141</td>
<td>0.89</td>
</tr>
<tr>
<td>Data miner</td>
<td>34</td>
<td>                   19</td>
<td>1.79</td>
</tr>
</tbody>
</table>
<p>Many terms were used outside the realm of data science. Other terms were used both in data science jobs and in jobs that require little analytic skill. Terms that could not be used to specifically find data science jobs were: analytics, data visualization, graphics, data graphics, statistics, statistical, survey, research associate, and business intelligence. One term, econometric(s), required deep analytical skills, but was too focused on one field.</p>
<p>The search terms that were well-focused on data science, but not overly focused in a single field are listed in the following table. The table is sorted by the number of jobs found on Indeed.com on February 26, 2017. While each column displays counts taken on a single day, the large size of Indeed.com’s database of jobs keeps its counts stable. The correlation between the logs of the two counts is quite strong, r=.95, p= 4.7e-14.</p>
<p>During this three-year period, the overall <a target="_blank" rel="nofollow" href="https://data.bls.gov/timeseries/LNS14000000">unemployment rate</a> dropped from 6.7% to 4.7%, indicating a period of job growth for most fields. Three terms grew very rapidly indeed with “data science” growing 7-fold, and both “data scientist” and “artificial intelligence” tripling in size. The biggest surprise was that the use of the term “statistician” took a huge hit, dropping to only 53% of its former value.</p>
<p>That table covers a wide range of terms, but only on two dates. What does the long-term trend look like? Indeed.com has a trend-tracking page that lets us answer that question. The figure below shows solid the growth in the percentage of advertisements that used the term “data scientist” (blue, top right), while those using the term “statistician” (yellow, lower right) are steadily declining.</p>
<p>The plot on the company’s site is interactive (the one shown here is not) allowing me to see that the most recent data points were recorded on December 27, 2016. On that date, the percentage of jobs for data scientist were 474% of those for statistician.</p>
<p><a target="_blank" rel="nofollow" href="https://i2.wp.com/r4stats.com/wp-content/uploads/2017/03/Indeed-Statistician-vs-Data-Scientist-2017.png"><img sizes="(max-width: 640px) 100vw, 640px" data-image-description="" data-orig-file="https://i2.wp.com/r4stats.com/wp-content/uploads/2017/03/Indeed-Statistician-vs-Data-Scientist-2017.png?fit=719%2C441" data-orig-size="719,441" data-image-title="Indeed Statistician vs Data Scientist 2017" class="wp-image-2086" data-comments-opened="1" data-recalc-dims="1" data-attachment-id="2086" data-permalink="http://r4stats.com/2017/03/13/jobs-for-data-science-up-7-fold-for-statistician-down-by-half/indeed-statistician-vs-data-scientist-2017/" alt="" data-medium-file="https://i2.wp.com/r4stats.com/wp-content/uploads/2017/03/Indeed-Statistician-vs-Data-Scientist-2017.png?fit=300%2C184" data-large-file="https://i2.wp.com/r4stats.com/wp-content/uploads/2017/03/Indeed-Statistician-vs-Data-Scientist-2017.png?fit=640%2C393" data-image-meta="{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}" src="https://i2.wp.com/r4stats.com/wp-content/uploads/2017/03/Indeed-Statistician-vs-Data-Scientist-2017.png?resize=640%2C393"></a></p>
<p>As an <a target="_blank" rel="nofollow" href="http://www.amstat.org/ASA/Your-Career/Accredited-Members.aspx">accredited professional statistician</a>, am I worried about this trend? Not at all. Statistical analysis software has broadened its scope to include many new capabilities including: machine learning, artificial intelligence, Structured Query Language, advanced visualization techniques, interfaces to Python, R, and Apache Spark. The software has changed because the job known as “statistician” has changed. Statisticians aren’t going away, their jobs are evolving into what we now know as data science. And that field is growing quite nicely!</p>
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