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[null,null,"Titolo",null,"Non-Academic Careers for Quantitative Social Scientists : A Practical Guide to Maximizing Your Skills and Opportunities / / edited by Natalie Jackson"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"9783031350368"]
[{"$nulls":4},"3031350367"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (206 pages)"]
[null,null,"Collana",null,"Texts in Quantitative Political Analysis, , 2730-9622"]
[null,null,"Disciplina",null,"320.0721"]
[{"$nulls":4},"300.23"]
[null,null,"Soggetti",null,"Political science"]
[{"$nulls":4},"Social sciences - Statistical methods"]
[{"$nulls":4},"Statistics"]
[{"$nulls":4},"Methodology of Political Science"]
[{"$nulls":4},"Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy"]
[{"$nulls":4},"Statistics in Business, Management, Economics, Finance, Insurance"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Chapter 1. Introduction: Surveying the Landscape of Industry Jobs -- Section 1: Career Paths -- Chapter 2. Data Science Needs You, Social Scientist -- Chapter 3. How to Thrive in the Data Industry Without a Traditional STEM Background -- Chapter 4. Alt-Academic Career Paths -- Chapter 5. From the Academy to Tech Startups: Considerations and Opportunities -- Chapter 6. Opportunities and Pathways in Survey Research -- Chapter 7. Market Research with a PhD in Sociology -- Chapter 8. Say Yes to Cultivating Your Future -- Chapter 9. Working in Government -- Chapter 10. Working in Quasi-Governmental Research -- Chapter 11. Proudly Disinterested: Public Administration and Social Science Ph.D. Programs -- Chapter 12. Applying the Transferrable Skill Set of a Ph.D. to Emerging Data Fieldsx -- Section 2: Advice for Non-Academic Job Success -- Chapter 13. How to Market Yourself for Careers Beyond the Professoriate -- Chapter 14. Beyond Visa Sponsorship: Navigating the Job Market as An Immigrant -- Chapter 15. So You Want to Work in Tech. How Do You Make the Leap? -- "]
[{"$nulls":4},"Chapter 16. Perspectives on Rapid Antigen Tests for Downstream Validation and Development of Theranostics -- Chapter 17. Kill, Pivot, Continue: Tips and Tricks for Career Transition Away From Academe -- Chapter 18. Presenting Academic Research in the Interview Process and Beyond: A Conversation Between Colleagues -- Chapter 19. Thriving in a Non-Academic Environment -- Chapter 20. You Got Your First Job, What About Your Second? Conversations with Women Social Scientists on Landing Multiple Non-Academic Jobs -- Chapter 21. Staying Academically Relevant in a Non-Academic Career.-."]
[null,null,null,"Sommario/riassunto","This book is a guide to non-academic careers for quantitative social scientists. Written by social science PhDs working in large corporations, non-profits, tech startups, and alt-academic positions in higher education, this book consists of more than a dozen chapters on various topics on finding rewarding careers outside the academy. Chapters are organized in three parts. Part I provides an introduction to the types of jobs available to social science PhDs, where those jobs can be found, and what the work looks like in those positions. Part II creates a guide for social science PhDs on how to set themselves up for such careers, including navigating the academic world of graduate school while contemplating non-academic options, and selling their academic experience in a non-academic setting. Part III offers perspectives on timelines for making non-academic career decisions, lifestyle differences between academia and non-academic jobs, and additional resources for those considering a non-academic route. Providing valuable insight on non-academic careers from those who have successfully made the transition, this volume will be an asset to graduate students, advisors, and recent PhDs, in quantitative social science. ."]