Matthew Nelson, PhD

Conduct quantitative research for Amazon's Reputation Marketing & Insights team — measuring brand perception, executive favorability, and competitive standing globally.

• Design large-scale survey programs tracking reputational outcomes over time
• Build automated data pipelines and reporting — crosstabs, visualization decks, and briefs for senior leaders
• Model perception drivers with logistic regression, Shapley-value attribution, and specification-curve robustness
• Turn analysis into localized, country-level strategy reports tailored to each market's context
• Bring vendor analytics in-house and manage cross-vendor calibration — cutting cost while protecting data integrity
• Apply machine learning and AI tools to automate processing and synthesize insight at scale

Delivered quantitative research and strategic counsel for Fortune 50 companies navigating reputation risk, competitive pressure, and crisis communications.

• Designed survey instruments and statistical models informing high-stakes brand and communications decisions
• Produced research briefs and executive presentations translating data into clear strategic direction
• Led internal training on research methodology and applied AI tools

Research on electoral institutions, redistricting, and voting rights — published in peer-reviewed journals and cited before the U.S. Supreme Court.

• Published in PS: Political Science & Politics; cited in Supreme Court amicus brief, Moore v. Harper
• Applied regression analysis, ecological inference, and racially polarized voting methods to redistricting cases
• Research covered by the Washington Post, FiveThirtyEight, and CalMatters