Charlotte Mines

Charlotte Mines is a Data Analyst in Universalia’s Organizations & Partnership Performance practice area. She supports the full spectrum of evaluation and monitoring services, including drafting proposals, designing evaluation tools, conducting data collection, performing quantitative and qualitative analysis, reporting writing and client-facing presentations. She has contributed to evaluation mandates for UN agencies, private sector corporations, and NGOs, including the World Food Programme (WFP), UNICEF, and Siemens. In her role, Charlotte leverages a wide range of data analysis methods, along with advanced technical writing and strong communication skills, to support evaluation design, execution, and presentation. She plays a key role in methodology design and brings innovative strategies to data analysis and collection, with experience designing surveys, interview protocols, machine learning tools, and advanced regression modeling in service of evaluations. She also brings thematic expertise in emerging economies, migration and remittances, informal financial systems, cash transfers, and political behavior.

Prior to joining Universalia, Charlotte pursued diverse experiences in international development, education, psychology, politics, and service across the US, Canada, and Amman, Jordan. During her graduate studies at McGill University, she balanced research and teaching commitments, honing skills in computer science, research design, international relations, machine learning, and textual analysis. Her master’s thesis examined state-community relations in coca-growing regions of Bolivia and Peru, exploring the dynamics between economic policy and cultural traditions in marginalized communities. Charlotte is skilled in many softwares and programmes, including Python, R, Nvivo, Dedoose, PowerBI, SQL, Stata, Qualtrics and Excel.

Born and raised in Boston, MA., Charlotte is globally educated, with working proficiencies in both Spanish and French, and conversational Arabic, in addition to her native English.