Ukeme Edward Eniang

Designed and implemented ETL pipelines using Apache NiFi, improving data processing efficiency.Built predictive models to optimize financial data analysis, enhancing decision-making.Conducted statistical analysis on financial trends, leading to actionable insights for policy recommendations.Automated data reporting with Python & SQL, reducing manual work by 4 hours per week.Developed interactive dashboards (Power BI, Tableau) for real-time financial monitoring.

Designed and deployed recommendation systems for subsidiary platforms, driving user engagement for subsidiary.Deployed social media traffic forecasting models, increasing content strategy efficiency by 25%.Achieved analyzed user behavior to identify key metrics for growth, enabling a 20% improvement in retention.

Worked on advanced seismic data analysis projects, applying machine learning and computer vision techniques to extract insights from large-scale geophysical data.Designed and trained deep learning models for fault detection and segmentation in seismic volumes.Built automated pipelines for training and retraining ML models to improve segmentation accuracy.Developed algorithms for object detection and localization in 3D seismic datasets.Reconstructed ground truth data from legacy systems using custom algorithms for improved model validation.Created ML modules for 3D object segmentation and integration into legacy workflows.Designed an interactive tool for fault grouping and visualization in 3D environments.Built a desktop application (.exe) to provide a user-friendly interface for all ML and computer vision modules.