Senior Researcher II

Fors Marsh seeks Senior Researcher II to work in Hamden, Connecticut.

Duties include : Design and execute election administration survey research across a variety of quantitative and qualitative methodologies and interpret results in the context of specific state laws and policies on election administration. Execution of advanced data analysis methods on large and complex election datasets (e.g., voter history files) containing transactional or administrative data. Coordinate the preparation and fielding of establishment surveys. Develop election administration research reports, presentations, and data visualizations. Plan all phases of election administration research projects, coordinating and supervising election researchers to complete the project's milestones, and coordinating with public sector clients (e.g., U.S. Election Assistance Commission and state / local election offices) and stakeholders for the duration of the project. Provide support to federal clients, including the U.S. Election Assistance Commission and the Federal Voting Assistance Program and build long-term relationships. Contribute to business development efforts and proposal writing for election administration survey research projects. Supervise Survey Researchers.

Must have : Master's degree in Public Policy, Public Administration, Political Science or other social science field, subject matter expertise on the topic of election administration demonstrated through conference presentations or publications with 24 months of experience with : (1) working on election administration research projects with federal clients like the U.S. Election Assistance Commission and the Federal Voting Assistance Program; (2) election-related establishment surveys (building, fielding, and analyzing data from these types of surveys) as well as managing and analyzing large and complex election datasets (e.g., voter history files) containing transactional or administrative data; and (3) creating public use datasets and building longitudinal datasets.

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