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Analysis of skills and qualifications required in data scientist job postings based on the pareto analysis perspective using text mining

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Akademik Birimler

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Yılmaz, Dilek Özdemir

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Işığıçok, Erkan
Çelik, Sadullah
Yılmaz, Dilek Özdemir

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İstanbul Üniversitesi

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Today, there are more job posts than ever before, making it incredibly challenging for job searchers to find the position that best suits them. To overcome this difficulty, text mining methods can be used to extract information such as job titles, required skills, and required experience, and to analyze job postings. This information can also be used to match job seekers with the most relevant job postings. The main purpose of this research is to determine which skills, techniques, subjects, fields, and so on should be prioritized by job seekers. For this purpose, 200 data scientist job postings from Turkey and 200 data scientist job postings from the USA are analyzed. According to the results, employers who have announced their interest in hiring a Data Scientist prefer people who are experts in Machine Learning, Data Science, Python, SQL, R, Statistics, and Mathematics, people with BSc, MSc, and PhD education levels, people with 3+ years of work experience, and people who know Visualization, Data Mining, Prediction, NLP, and Clustering techniques. For this reason, it is recommended that people who want to become data scientists in TR or the USA improve themselves in these techniques, skills, and experiences to be accepted to data scientist position jobs more easily.

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Data scientist, Job postings, Text mining, Document-term matrix, Pareto analysis, Social sciences, Science & technology, Physical sciences, Economics, Statistics & probability, Business & economics, Mathematics, Keyword

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