Independent analytical work: Consumer Mood & Trend Analyzer and related Python models (consumer decision signals, prioritization, budget optimization).
Other
Built Python-based analysis tools to extract and interpret sentiment signals from public data sources for consumer trend understanding. Implemented structured workflows that transform raw inputs into analyzable signals using basic statistical reasoning. Documented outputs as research-ready artifacts to support hypothesis-driven insight synthesis. • Developed a sentiment signal extraction and processing pipeline in Python from public data sources. • Conducted exploratory pattern analysis to identify recurring trends and anomalies. • Designed algorithmic frameworks for decision support using weighted scoring and prioritization logic. • Created simulation/modeling components to support budget allocation and multi-criteria comparisons.
2024 - 2025