• Data Science
  • Daniel Gutierrez
  • FEB 13, 2018

Top Skills Data Scientists Need To Learn in 2018

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Data scientists are in high demand, taking the number 1 spot in Glassdoor’s Best Jobs in America list in 2016 and 2017, with 4,84 position available and boasting a median base salary of $110,000. DevOps engineer came in second, with a median base salary of $110,000 and 2,725 job openings. Data engineer rounded out the top three, with 2,599 job openings and a median base salary of $106,000. Data science jobs are among the most challenging to fill, taking five days longer to find qualified candidates than the market average. Employers are willing to pay premium salaries for professionals with expertise in these areas as well.  The most in-demand jobs in data science require advanced education, further driving up demand and salaries for professionals with these qualifications.

Source: http://blogs-images.forbes.com/louiscolumbus/files/2017/05/Combined-graphic-of-skills.jpg

According to Jim Webber, Chief Scientist at Neo4j, the following is a short-list of the most essential tech skills for data scientists to adopt this year:

  • Spark: Spark is transforming how data scientists work by allowing interactive and iterative data analysis at scale. Data scientists who are familiar with Spark will be more attractive to companies in 2018, as this tool help reduce costs, increase profits, improve products, retain customers and identify new opportunities.
  • Apache Mahout: Data science and analytics job demand is most prominent in the financial services industry, accounting for 19 percent of all openings. This is largely due to the growing concern about security on Wall Street, which has resulted in companies hiring data scientists to solve issues such as cyber security breaches and identity theft. Data scientists who can work with machine learning models and frameworks, such as Mahout, will be in high demand.
  • Graph databases: Graphs are the fastest-growing category in database management systems and tech giants like AWS, Oracle and IBM all have graph offerings. Gartner predicts that 70% of leading companies will pilot a graph database project of significance by 2018. With this uptick in graph database usage, familiarity with the technology will be key. Data scientists who have the knowledge to deploy and manage graph databases to find connections within their data will be best positioned for the top jobs in the industry.
  • Tableau: Business data is growing at an exponential rate. With this great data comes great power, so long as you can understand it. While Tableau isn’t a new product by any means for data scientists, it’s almost a table-stakes skill at this point. With business decision-makers relying more heavily on their data insights than ever before, 2018 will bring a greater need for data scientists to visualize and present data to the right people at the right time.
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