Sr. Political Researcher

Posted about 15 hours agoViewed
157000 - 196000 USD per year
United StatesFull-TimePolitical Data
Company:GoodParty.org
Location:United States
Languages:English
Seniority level:Senior, 5+ years
Experience:5+ years
Skills:
PythonSQLArtificial IntelligenceData AnalysisData MiningGitMachine LearningNumpyData sciencePandasAnalytical SkillsProblem SolvingResearchData visualizationData modeling
Requirements:
5+ years of relevant experience; or a master’s degree in a quantitative or social science field and 3+ years of applied work experience; or a PhD with evidence of experience working quickly with concrete deliverables. Strong background applying data science, statistics, or computation to politics. Experience with public opinion data: either designing and fielding surveys or analyzing data sources on public opinion or behavior and imputing data. Experience designing and deploying field experiments. Experience with forecasts, predictions, or inferential models about politics. Hands-on experience with U.S. election data or other types of U.S. political data. Ability to scope questions, choose methods, ship analyses, and iterate independently. Used a statistical programming language (preferably R or Python) in a previous role. Comfortable writing queries in SQL. Experimented with how cutting-edge AI models can be used to address political data and research questions.
Responsibilities:
Develop, test, and refine quantitative models of electoral outcomes. Model constituencies and public service outcomes. Implement and iterate on public opinion measurement methods. Design and run surveys and political field experiments. Find opportunities for natural experiments in data. Improve measurements of electoral and public service outcomes. Identify new data sources and improve usage of existing data. Partner with engineering, operations, and product teams. Enhance product features for candidates and public officials. Work independently as a senior member of a small research team. Own a cycle of constant model improvement.
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