Data Analyst

Designed three Power BI dashboards for monitoring field operations, quality control, and interventions requiring verification. Built a dashboard connecting technicians and supervisors, including a consistency-scoring system to prioritize interventions for review.

Automated data cleaning, sampling, and joins with Power Query, reducing production time for five carbon-certification files from four hours to 15 minutes. Developed and evaluated a Python machine learning model to predict planted-species mortality and identify survival factors for agroforestry loss-reduction actions.

Contributed to DIP-MD, an analytics platform using economic and financial data from 6–8 UEMOA countries, delivering eight analytical features. Built data-driven classification, segmentation, and scoring capabilities alongside macroeconomic analysis and geospatial visualizations.

Developed Python ETL pipelines to integrate, clean, and transform data for analysis and visualization. Implemented automated pipeline testing to improve reliability and detect issues in data workflows.

Developed an AI model for pothole detection and classification, achieving an estimated accuracy of 89%. Contributed to a functional prototype for identifying road damage and supporting road-network management.

Coordinated technical activities in a team of four to five people in an Agile environment. Facilitated task organization and supported development progress.