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9 Must-Have Skills You Need to Become a Data Scientist

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Burtch Works details the top 9 data science skills that potential data scientists must have to be competitive in this growing marketplace from the perspective of a recruiter.

Non-Technical Skills

  1. Intellectual curiosity – No doubt you’ve seen this phrase everywhere lately, especially as it relates to data scientists. Frank Lo describes what it means, and talks about other necessary “soft skills” in his guest blog posted a few months ago.
  2. Business acumen – To be a data scientist you’ll need a solid understanding of the industry you’re working in, and know what business problems your company is trying to solve. In terms of data science, being able to discern which problems are important to solve for the business is critical, in addition to identifying new ways the business should be leveraging its data.
  3. Communication skills – Companies searching for a strong data scientist are looking for someone who can clearly and fluently translate their technical findings to a non-technical team, such as the Marketing or Sales departments. A data scientist must enable the business to make decisions by arming them with quantified insights, in addition to understanding the needs of their non-technical colleagues in order to wrangle the data appropriately. Check out our recent flash survey for more information on communication skills for quantitative professionals.

Computer and Book

The next question I always get is, “What can I do to develop these skills?” There are many resources around the web, but I don’t want to give anyone the mistaken impression that the path to data science is as simple as taking a few MOOCs. Unless you already have a strong quantitative background, the road to becoming a data scientist will be challenging – but not impossible.

However, if it’s something you’re sincerely interested in, and have a passion for data and lifelong learning, don’t let your background discourage you from pursuing data science as a career. Here are a few of the resources we’ve found to be helpful:


  1. Advanced Degree – More Data Science programs are popping up to serve the current demand, but there are also many Mathematics, Statistics, and Computer Science programs.
  2. MOOCsCoursera, Udacity, and codeacademy are good places to start.
  3. Certifications – KDnuggets has compiled an extensive list.
  4. Bootcamps – For more information about how this approach compares to degree programs or MOOCs, check out this guest blog from the data scientists at Datascope Analytics.
  5. KaggleKaggle hosts data science competitions where you can practice, hone your skills with messy, real world data, and tackle actual business problems. Employers take Kaggle rankings seriously, as they can be seen as relevant, hands-on project work.
  6. LinkedIn Groups – Join relevant groups to interact with other members of the data science community.
  7. Data Science Central and KDnuggetsData Science Central and KDnuggets are good resources for staying at the forefront of industry trends in data science.
  8. The Burtch Works Study: Salaries of Data Scientists – If you’re looking for more information about the salaries and demographics of current data scientists be sure to download our data scientist salary study.

I’m sure there are items I may have missed, so if there’s a crucial skill or resource you think would be helpful to any data science hopefuls, feel free to share it in the comments below!

Original: http://www.burtchworks.com/2014/11/17/must-have-skills-to-become-a-data-scientist/


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