Uche Onyibe

I’m a Data Analyst with 5 years of experience extracting, manipulating, and presenting data from relational databases. I build end-to-end data products using SDLC methodologies like Agile and Waterfall, with a strong focus on data warehousing phases such as cleansing, mining, and modeling.

I engineer and deploy predictive models—like Logistic Regression and Random Forest—using Python (NumPy, SciPy) to forecast revenue trends and technician capacity. In one role, I improved planning accuracy by 7% through advanced statistical methods, and I’ve driven measurable gains in forecasting and decision quality.

I turn complex outputs into business impact through visualization and communication. I designed interactive Tableau dashboards to make machine learning results actionable for stakeholders, and I architected an end-to-end NLP pipeline using Transformer-based models (BERT/RoBERTa) and LDA topic modeling, improving Net Promoter Score (NPS) by 15% over 6 months.

I also focus on production-ready automation and efficiency. I developed a real-time sentiment analysis system with Python, FastAPI, and Docker that triaged 500k+ monthly support tickets with 94% accuracy and reduced average manual response time by 40%.