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Trends in Data Science Hiring

... Ramya Krishnan

Data analysts are in extremely high demand right now. The number of data scientists has doubled over the last 4 years (LinkedIn Study). This increase in supply side reflects a direct response to the rapid ramp-up in demand for data scientists for various roles requiring sophisticated data analysis skills, combining computer programming with statistics. Based on data and reports available by LinkedIn, RJMetrics, Udacity Indeed etc. we have analysed the emerging trends in Data Science hiring.

Industries Hiring Data Scientists: The five leading industries with the most job openings requiring big data expertise include Professional, Scientific and Technical Services (27.14%), Information Technologies (18.89%), Manufacturing (12.35%), Retail Trade (9.62%) and Sustainability, Waste Management WM -0.23% & Remediation Services (8.20%). The following graphic shows the distribution of open positions (Source Forbes):

top 20 industries hiringCompanies Hiring Data Scientists: The top ten companies employing data scientists are:

  1. Microsoft,
  2. Facebook,
  3. Google,
  4. IBM
  5. Amazon
  6. Twitter
  7. Nielsen,
  8. GE,
  9. Apple,
  10. LinkedIn,

Other leading companies who have been aggressively hiring people for Data Science roles include, Teradata, Accenture, Pramerica, Dropbox, Tableau, Booz Allen Hamilton, GlaxoSmithKline,

Different Data Science Roles being Hired: Data science roles and responsibilities are diverse and skills required for them vary considerably. Some of the important Data Science roles which are in demand are:

  • The Data Scientist
  • The Data Analyst
  • The Business Analyst
  • The Data Architect
  • The Data Engineer
  • The Statistician
  • The Database Administrator
  • Data and Analytics Manager

Data Science Skills Getting Hired : Based on indeed.com date, the top Data Science skills which is getting hired  are:

  • SAS
  • Python,
  • R,
  • C++
  • NoSQL,
  • MATLAB,
  • Java,
  • Statistical modeling,
  • Hadoop
  • Spark
  • Visualisation

Academic Qualification of the Hires: For top end jobs at top level companies like Google Facebook etc. the requirement is generally for advanced degree (Ph.D. or Master’s) in an analytical or technical field (e.g. applied mathematics, statistics, physics, computer science, operations research or relate fields).However, at this point, many companies are willing to hire people with peripheral degree to Data Science as Only 4.6% of data scientists have machine learning/data science as their MS degree. As this number increases in coming years due to the proliferation of new Master in Data Science programs, one expects that companies will insist on an MS Degree in Machine Learning/Data Science.

ALSO READ: How to Become a Data Scientist

Given the lack of qualified people, companies are also substituting qualification with experience and looking for hands-on experience in working with very large datasets; experience with data mining tools; strong mathematical and statistical background; and programming skills in Java/PHP or other languages.

ALSO READ: 5 Steps To Switch Your Career To Analytics

Relevant For

Big Data Hadoop Data Science