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Using Science to Support and Develop Employees in the Tech Workforce — An Opportunity for Multidisciplinary Pursuits in Engineering Education

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 5

Tagged Division

Multidisciplinary Engineering Division (MULTI)

Tagged Topic

Diversity

Page Count

10

DOI

10.18260/1-2--44581

Permanent URL

https://peer.asee.org/44581

Download Count

194

Paper Authors

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Marina Dias

biography

Sreyoshi Bhaduri Amazon

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Dr. Sreyoshi Bhaduri is an Engineering Educator and People Research Scientist. As a Research Scientist at Amazon, Sreyoshi leverages AI and mixed-methods research on and for people at work, ensuring that organizations intentionally center the human experience. Sreyoshi has a doctorate in Engineering Education, and Masters degrees in Applied Statistics (M.A.) and Mechanical Engineering (M.S.). She earned her Bachelors degree in Mechatronics Engineering from Manipal University in India. Sreyoshi has been recognized as a Fellow at the Academy for Teaching Excellence at Virginia Tech (VTGrATE) and a Fellow at the Global Perspectives Program (GPP) and was inducted to the Yale Bouchet Honor Society during her time at Virginia Tech. She has also been honored as an Engaged Advocate in 2022 and an Emerging Leader in Technology (New ELiTE) in 2021 by the Society of Women Engineers. Sreyoshi is passionate about improving belonging among women in Engineering. She serves as Senator at SWE (Society of Women Engineers) - the world’s largest advocate and catalyst for change for women in engineering and technology with over 42,000 global members. She also champions and serves as advisor at Sisters in STEM - a not-for-profit led by school students, aimed at increasing interest, engagement, and allyship in STEM. Learn more about her work at - www.ThatStatsGirl.com

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Amulya Mysore

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Amulya is a Data Scientist at Amazon. She is passionate about learning how data driven decisions can bring about tangible outcomes in the real world with the help of experimentation and statistical modelling. She has previously worked at Discover Inc and American Express and has a master’s degree in computer science from Arizona state university.

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Wanqun Zhao

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Amelia Rivera-Burnett

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Amelia Rivera-Burnett is a Senior Product Manager at Amazon. As a Product Manager, she is responsible for defining product vision, prioritizing customer requirements and working cross functionally with partner teams (e.g., Engineering, Science, Analytics) to deliver differentiated product experiences. Amelia has a passion for experimentation and has a fifteen year background in advertising. She earned her Bachelor's degree in English from Fordham University in New York.

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Shahriar Sadighi

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Robert Pulvermacher

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Dr. Robert Pulvermacher is a Research Program Manager at Amazon. He is responsible for directing and supporting research streams around talent management practices and aligning research outcomes with UX, Data Science, Economist, and BIE teams. Robert previously worked as an Associate Director at Gartner and Senior Associate at KPMG. He has a Ph.D. in I/O Psychology from Northern Illinois University.

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Abstract

Engineering education does not end in universities since engineers continue to learn, advance, and develop as professionals in the workforce. This presents an opportunity for engineering education research within tech companies to help employees with their career journeys from onboarding onto teams to exiting teams or exploring new roles. Specifically, this paper draws from multi-disciplinary experiences of researchers, including an engineering educator, two economists, and a program and product manager to present lessons from leading with science to understand, inform, and better employee careers at a global tech company. The purpose of this paper is to elaborate on the opportunity for mixed methods research at the intersections of professional development, employee careers, science, product, and engineering. We present an overview of cutting edge technologies that leverage employee data to inform decision making on talent management. This paper describes interdisciplinary sciences collaborate to understand employees in the tech workforce. It also documents best practices to deal with common challenges in conducting research leveraging data on professionals in the tech industry, including communicating with and educating stakeholders and partners, understanding employee sentiment, and improving products, program, and technology to augment career progression. Finally, this paper highlights an opportunity for engineering education to influence the future of tech workforce.

Dias, M., & Bhaduri, S., & Mysore, A., & Zhao, W., & Rivera-Burnett, A., & Sadighi, S., & Pulvermacher, R. (2023, June), Using Science to Support and Develop Employees in the Tech Workforce — An Opportunity for Multidisciplinary Pursuits in Engineering Education Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44581

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