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ClassificationResearch Assistant – Data Cleaning and Annotation (Peer-Reviewed Publication). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Doctor of Philosophy, City, University of London (2025) and Master of Science, Girne American University (2017). AI-training focus includes data types such as Text and labeling workflows including Classification, Evaluation, and Rating.
Writing prompts in 4 - 6 to six turns and Identify the model that is better by selecting weaknesses
Applied difference-in-differences methodology to large administrative microdata, requiring design and evaluation of synthetic counterfactual scenarios. Systematically assessed outputs of economic models against rigorous academic criteria. Created annotated datasets for causal inference and quality evaluation in AI-supported econometric research. • Built evaluation protocols for microdata output quality • Specified annotation requirements and conditions in research workflows • Reviewed outputs for accuracy and compliance with research standards • Automated aspects of the evaluation process using structured tools
Conducted detailed econometric analysis involving systematic identification and classification of data inconsistencies. Led data cleaning, regression modeling, and robustness checks on large-scale, complex text datasets. Developed quality assessment criteria for consistency and reliability in annotated output. • Designed annotation protocols for structured economic datasets • Identified and corrected labeling errors using manual and automated checks • Applied advanced econometric models to classified text data • Ensured data integrity through rigorous review processes
Master of Science, Economics
Bachelor of Science, Economics
Executive Assistant & Strategic Projects Lead
Project Manager – Operations & Procurement
