Resumen

BHORE, Milind  y  TAPAS, Poornima. An exploratory study of factors influencing career decisions of Generation Z women in Data Science. SAJHRM [online]. 2023, vol.21, pp.1-9. ISSN 2071-078X.  http://dx.doi.org/10.4102/sajhrm.v21i0.2168.

ORIENTATION: Since April 2022, there has been a 30% increase in Data Science job openings globally. The majority of these positions are filled by Generation Z talent (Gen Z). According to research, businesses that promote gender diversity have higher earnings and revenues. RESEARCH PURPOSE: The purpose of this study is to identify factors that will help organizations in designing policies and work environment to attract and foster Gen Z women employees in Data Science. MOTIVATION FOR THE STUDY: There is limited research focusing on Gen Z women professionals and factors influencing their career choices in the field of Data Science in the Indian context. RESEARCH APPROACH/DESIGN AND METHOD: Structured questionnaire was distributed online. Purposive sampling technique was adopted and 216 responses from Gen Z women studying in technology institutes pan India and working in Data Science were collected. Multiple linear regression statistical technique was leveraged for data analysis. MAIN FINDINGS: Technical education, job opportunities, compensation and conducive environment significantly and positively influence career decisions of Gen Z women in Data Science. PRACTICAL IMPLICATIONS: Organizations will be able to define policies to encourage hiring of Gen Z women, break stereo types that prevent women from pursuing career in Data Science and create a conducive work environment that acknowledges and rewards the performance of Gen Z women. CONTRIBUTION/VALUE-ADD: The findings of this study will encourage more women from Gen Z to pursue careers in Data Science, boosting gender diversity and inclusivity in Data Science.

Palabras clave : Gen Z women; career; Data Science; technology; Science, Technology, Engineering, and Mathematics (STEM).

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