Darel Evrard Kigha Mohmbah

- Reviewed and analyzed existing data ingestion scripts to understand data fetching, processing, and storage workflows. - Implemented GitHub Actions to automate test runs, ensuring reliable and consistent data pipeline execution. - Refactored scripts into modular fetch, transform, and load components to support daily automated updates. - Documented the complete pipeline setup, workflow structure, and maintenance procedures to support future development and collaboration

- Implemented data management practices, removing errors and outliers to ensure data integrity. - Performed data interpretation and created clear visuals to derive meaningful conclusions. - Streamlined data processing workflows with Python scripts to automate data ingestion for efficiency

- Inspected 50-100 products daily and streamlined intake documentation, improving inventory accuracy and minimizing input errors. - Collaborated with a team of 3 to consistently exceed daily fulfillment targets by 10-15%, supporting overall warehouse efficiency.

- Executed precise product scans for inventory management, contributing to a 99.5% accuracy rate in stock levels and efficient order processing for orders daily. - Contributed to optimizing order fulfillment workflows by identifying bottlenecks in sorting processes, leading to a reduction in average processing time per order. - Reduced product damage by 10% through improved packing protocols

Acquired hands-on experience through an immersive program, analyzing large datasets with Python, SQL, and Pandas to extract meaningful insights. Developed data-driven reports and visualization using Tableau, Power Bi, Looker Studio, and Matplotlib, enhancing business intelligence and decision-making. Applied statistical analysis and predictive modeling techniques, implementing machine learning algorithms, regression models, and clustering methods to identify trends.