Glassdoor Job Description Analytics – Analyzing Data Science Professional Roles and Skills

Swapna Gottipati, Kyong Jin Shim, Sarthak Sahoo
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引用次数: 2

Abstract

With increasing data volume and adoption of technologies including machine learning and artificial intelligence across all industries, the demand for skilled Data Science professionals is continuing to increase globally. For educational institutions to teach the most up-to-date and industry-relevant skills and for businesses to hire employees with the right set of skills, it is important for them to stay tuned to the fast-changing dynamics of job landscape. In this research study, we present an NLP approach to the analysis of job listings from Glassdoor. Our solution mines insights on trending technical and soft skills in the Data Science job categories. Based on the insights, we provide recommendations to design overall data science curriculum learning outcomes (LOs). We also provide recommendations to the course designers on specific technical skills required for the topics of courses under the data science curriculum.
职位描述分析-分析数据科学专业角色和技能
随着数据量的增加以及各行各业对机器学习和人工智能等技术的采用,全球对熟练数据科学专业人员的需求不断增加。对于教育机构来说,要教授最新的和行业相关的技能,对于企业来说,要雇佣具有正确技能的员工,重要的是他们要时刻关注快速变化的就业前景。在这项研究中,我们提出了一种NLP方法来分析来自Glassdoor的职位列表。我们的解决方案挖掘了数据科学工作类别中趋势技术和软技能的见解。基于这些见解,我们提供了设计整体数据科学课程学习成果(LOs)的建议。我们还就数据科学课程下的课程主题所需的特定技术技能向课程设计者提供建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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