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Assessing the Effect of Workplace St...

Sardar, Muhammad,

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Assessing the Effect of Workplace Stress on Job Satisfaction of Data Science Professionals /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Assessing the Effect of Workplace Stress on Job Satisfaction of Data Science Professionals // Muhammad Sardar.
Author:	Sardar, Muhammad,
Description:	1 electronic resource (119 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-05, Section: B.
Contained By:	Dissertations Abstracts International86-05B.
Subject:	Information technology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31556754
ISBN:	9798342714006

Assessing the Effect of Workplace Stress on Job Satisfaction of Data Science Professionals /
Sardar, Muhammad,

Assessing the Effect of Workplace Stress on Job Satisfaction of Data Science Professionals /Muhammad Sardar. - 1 electronic resource (119 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

Stress is found to be a leading catastrophe in the present workforce as they are employed in the ever-evolving digital industry where software updates are increasingly making their skills redundant. This is especially true for data scientist professionals who are expected to have hands-on knowledge of multiple latest software and platforms simultaneously. Factors like job insecurity, cognitively demanding jobs, and increasingly high workloads often lead to significant stress among data scientist professionals, which may lead to low job satisfaction. Literature connecting stress and job satisfaction in different fields also emphasizes the importance of work-life balance, which is found to be less common among people who lack job satisfaction. Hence, the current study aims to understand the direct impact of workplace stress on the job satisfaction of data scientist professionals while testing the other factors for their moderating role, such as career development, social support and organizational commitment under PMI theory. The current study uses an online survey strategy to collect data from 346 data scientists or analysts and relies on a statistical regression analysis approach to test the hypotheses. Overall, the findings concluded that occupational stress significantly and negatively impacts job satisfaction. The results also revealed that this negative impact can be reduced if data scientist professionals feel their manager cares about their future and career development. The effect of organizational commitment and social support in the workplace positively and significantly impact the job satisfaction levels of data scientists and analysts. The results provide substantial managerial implications to keep data scientist professionals motivated and satisfied in their jobs by working on factors like career development through training and encouraging teamwork for social support.

English

ISBN: 9798342714006Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Data scientists

Assessing the Effect of Workplace Stress on Job Satisfaction of Data Science Professionals /
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520 $a Stress is found to be a leading catastrophe in the present workforce as they are employed in the ever-evolving digital industry where software updates are increasingly making their skills redundant. This is especially true for data scientist professionals who are expected to have hands-on knowledge of multiple latest software and platforms simultaneously. Factors like job insecurity, cognitively demanding jobs, and increasingly high workloads often lead to significant stress among data scientist professionals, which may lead to low job satisfaction. Literature connecting stress and job satisfaction in different fields also emphasizes the importance of work-life balance, which is found to be less common among people who lack job satisfaction. Hence, the current study aims to understand the direct impact of workplace stress on the job satisfaction of data scientist professionals while testing the other factors for their moderating role, such as career development, social support and organizational commitment under PMI theory. The current study uses an online survey strategy to collect data from 346 data scientists or analysts and relies on a statistical regression analysis approach to test the hypotheses. Overall, the findings concluded that occupational stress significantly and negatively impacts job satisfaction. The results also revealed that this negative impact can be reduced if data scientist professionals feel their manager cares about their future and career development. The effect of organizational commitment and social support in the workplace positively and significantly impact the job satisfaction levels of data scientists and analysts. The results provide substantial managerial implications to keep data scientist professionals motivated and satisfied in their jobs by working on factors like career development through training and encouraging teamwork for social support.
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