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What LinkedIn has to say about Machine Learning Engineers and Data Scientists

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Machine Learning Engineers and Data Scientists are the top two Emerging Jobs from 2012 to 2017 as reported in LinkedIn’s 2017 U.S. Emerging Jobs Report. Job titles on LinkedIn profiles that included Machine Learning increased by 980% and Data Scientist titles went up 650% from 2012 to 2017. This increase was less than the open positions available because there are currently only 35,000 people in the U.S. with data science skills. There were more than 1600 open roles for machine learning engineers at the end of 2017. Supply is not keeping up with demand.

Technology

Technology is the top of every list as THE growth industry and skill most needed to thrive in the coming years. Machine Learning Engineers and Data Scientists are significant players in the technology industry but LinkedIn reports “These jobs are also widely available outside of the technology industry.” LinkedIn goes on to say that many of the emerging roles in the top twenty require expertise in multiple disciplines and are applicable to multiple industries.

Where are these Machine Learning Engineers and Data Scientists coming from?

Advanced degree training in statistics and computer science is one source as evidenced by people transitioning from academic titles like Research Assistant and Teaching Assistant, but LinkedIn saw career growth from a number of other prior titles. Machine Learning Engineers came from titles that included Software Engineer, Research Assistant, Teaching Assistant, Data Scientist and System Engineer. Data Scientists evolved from titles that included Research Assistant, Teaching Assistant, Software Engineer, Data Scientist and Business Analyst.

 

Top Ten Skills of Data Scientists

As reported by Ferris Jumah of the American Statistical Association in the May 2018 Amstat News article, “Who Is the American Statistician? Or, Is It Data Scientist?” the top 10 skills of the Data Scientist are Data Mining, Machine Learning, R, Python, Data Analysis, Statistics, SQL, Java, Matlab and Algorithms. Mr. Jumah derived this information from people with the title of Data Scientist on their LinkedIn profile using TFIDF. TFIDF is short for term frequency-inverse document frequency. It is a numerical statistic that reflects how important a word is to a document.

 

The LinkedIn Emerging Jobs analysis focused on the skills most strongly represented in all the top twenty emerging jobs: Management, Sales, Communication, Marketing, Start-Ups, Python, Software Development, Analytics, Cloud Computing and Retail. So along with Python, Analytics and Cloud Computing, the successful Machine Learning Engineer and Data Scientist must have soft skills that allow them to effectively interact inside and outside their organization.

 

Interested in knowing more about getting into Machine Learning or Data Science? Contact the Data Science and Analytics Recruiters at Smith Hanley Associates.

Paul Chatlos, pchatlos@smithhanley.com, 203.319-4034
Nancy Darian, ndarian@smithhanley.com, 312.589-7582
Eda Zullo, ezullo@smithhanley.com, 203.319-4309

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