2 Surprises in Data Science Jobs

1. Surprise, the tools of data science, such as hadoop, python, and SAS, are far down on the popularity list of skills words. No surprise, the ideal candidate has experience, and uses computers and statistics. My take: hiring a data scientist is unfamiliar to most companies, so it feels risky. Managers are not confident of their hiring process. They dream of finding someone who has already successfully performed the exact tasks they need.

2. Surprise, business, team, and learn are among the most important descriptors for responsibilities.  No surprise that develop, research, analytic, algorithm, model are also among the most common terms. My take: Working with people (team, business, project, set, learn, custom,  support, inform, innovate ) is equally important to doing things to data (develop, model, research, algorithm, statistics, analyze).


The Data

Last week I collected 20 “Data Scientist” jobs posted on indeed.com. I pasted job responsibilities and desired skills into a text document, then cleaned and stemmed it. Descriptions of responsibilities had 1.5x words used to describe skills.

Published by Sue Aldrich

As a leading authority on worldwide customer requirements, practices, technologies, and governance for personalization, Sue researches the technologies and practices that help marketers get the most useful content in front of customers at the right moment: recommendations, search, discovery, targeted marketing, and web content management. Aldrich is an expert on optimizing the methods that help customers find what they need to make buying decisions and/or to solve problems. She helps clients develop personalization, marketing, discovery, and content management practices that will engage customers and improve results.

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