Chapter 41 Further Reading: Careers in Political Analytics

Understanding the Field and Its History

Nickerson, David W., and Todd Rogers. "Political Campaigns and Big Data." Journal of Economic Perspectives 28, no. 2 (2014): 51–74. One of the clearest and most accessible overviews of how political data analytics actually functions in campaign settings. Written by academic researchers who have worked directly with campaigns. Provides essential historical context for understanding how the field developed and what it has learned about effective voter mobilization.

Hersh, Eitan. Hacking the Electorate: How Campaigns Perceive Voters. Cambridge University Press, 2015. The most comprehensive academic study of campaign voter data use. Hersh's analysis of how campaigns use the voter file and commercial data to model the electorate is directly relevant to the targeting and modeling work that occupies most campaign analytics roles.

Sasha Issenberg. The Victory Lab: The Secret Science of Winning Campaigns. Crown, 2012. The accessible, narrative account of how behavioral science and data analytics transformed campaign strategy in the Obama era. While somewhat dated on specific tools and technologies, the fundamental story of how evidence-based campaigning emerged remains highly relevant and readable.

Professional Organizations and Resources

American Association for Public Opinion Research (AAPOR) — aapor.org. The primary professional organization for survey researchers. The website includes the Code of Professional Ethics, the Transparency Initiative member directory, job listings, and information about the annual conference. The AAPOR mentorship program connects early-career researchers with experienced practitioners.

American Political Science Association (APSA) — apsanet.org. The academic professional organization for political scientists. The eJobs listings are the primary source for academic positions; the Graduate Student and Early Career section provides resources for navigating academic career paths.

The Analyst Group (TAG) — analystgroup.org. The trade association for political data and analytics professionals. TAG publishes industry resources, maintains a member directory, and hosts events for practitioners in the campaign data ecosystem. Its ethical guidelines document is a useful complement to the AAPOR Code for non-polling analytics roles.

National Institute for Computer-Assisted Reporting (NICAR) / Investigative Reporters and Editors (IRE) — ire.org. The primary professional development organization for data journalists. The annual NICAR conference is the major networking and professional development event for data journalism practitioners. IRE's resource library includes training materials and tipsheets relevant to political analytics.

Career Development and Professional Navigation

Newport, Cal. So Good They Can't Ignore You: Why Skills Trump Passion in the Quest for Work You Love. Grand Central Publishing, 2012. Newport's argument — that career satisfaction comes from developing rare and valuable skills rather than from following passion — is particularly relevant for political analytics careers, where the most common mistake is optimizing for ideological fit over skill development.

Sandberg, Sheryl. Lean In: Women, Work, and the Will to Lead. Knopf, 2013. While its advice has been critiqued for focusing on individual behavior rather than structural barriers, the book's analysis of how informal networks, mentorship gaps, and confidence differentials shape career trajectories is directly relevant to the diversity challenges in political analytics described in Chapter 41.

Bohnet, Iris. What Works: Gender Equality by Design. Harvard University Press, 2016. A research-based analysis of what organizational interventions actually improve diversity outcomes (as opposed to what organizations do because it feels good but doesn't work). Relevant both for individuals navigating the field and for hiring managers trying to improve the diversity of their organizations.

Diversity and Inclusion in Technical Fields

Roberts, Dorothy. Killing the Black Body: Race, Reproduction, and the Meaning of Liberty. Vintage, 1999. Though not specifically about political analytics, Roberts' analysis of how technical and scientific systems can embed racial hierarchy provides essential historical and intellectual context for understanding why diverse leadership in data-driven fields matters.

Williams, Joan C. White Working Class: Overcoming Class Cluelessness in America. Harvard Business Review Press, 2017. Relevant to the diversity challenge in political analytics from the dimension of class as well as race: the field's concentration among elite educational institutions reflects class barriers that are distinct from but related to racial barriers.

Dowd, Kelly, and Tarah Wheeler. "Diversity in Political Analytics: A 2022 Landscape Survey." Analyst Group White Paper, 2022. If available, this industry self-assessment provides quantitative data on the demographic composition of the political analytics workforce — a useful evidence base for evaluating the diversity arguments in Chapter 41.

Career Transitions and Non-Linear Paths

Ibarra, Herminia. Working Identity: Unconventional Strategies for Reinventing Your Career. Harvard Business Review Press, 2003. Ibarra's research on how professional identity changes during career transitions is particularly relevant for the political analytics practitioners who move between sectors — from campaign to civic tech, from academic to applied, from commercial to government — over the course of a career.

Kramer, Michael, and Marc Hetherington. Prius or Pickup? How the Answers to Four Simple Questions Explain America's Great Divide. Houghton Mifflin Harcourt, 2018. The chapter authors recommend this as not primarily a career book but as a model for communicating complex quantitative political science research to a general audience. Reading books that successfully translate political science for public consumption is one of the best ways to develop the communication skill that Chapter 41 identifies as a genuine career differentiator.

Civic Technology and Public Interest Tech

O'Mara, Margaret. The Code: Silicon Valley and the Remaking of America. Penguin Press, 2019. Provides essential historical context for understanding how the technology industry and its values developed in the United States — context that is important for understanding both the civic technology sector and the commercial technology infrastructure that political analytics now relies on.

Taddonio, Patrice. "Inside the Effort to Get More People of Color Into Tech." FRONTLINE, 2019. Documents the structural barriers to diversity in technology and civic technology specifically, with direct relevance to the internship accessibility and hiring network problems described in Chapter 41.

Code for America — codeforamerica.org. The organization's website includes job listings, fellowship information, and extensive documentation of their work. Reading their project documentation provides a realistic picture of what civic technology work involves.

Salary and Labor Market Data

Campaign and Elections Magazine — campaignsandelections.com. The industry trade publication for political campaign professionals. Periodic salary surveys provide the most current available data on compensation in campaign analytics and political consulting roles.

APSA's Faculty Compensation Survey. Published periodically by APSA, provides data on academic political science salaries by rank, institution type, and specialty. Available through the APSA website.

Bureau of Labor Statistics Occupational Outlook Handbook — bls.gov/ooh. The market-analyst and political scientist entries provide baseline labor market data, though the categories don't map cleanly onto the specific roles in political analytics. Useful for benchmarking against the broader analytical labor market.