Rohith Abraham

I’m a Data Science graduate and detail-oriented Data Analyst focused on developing end-to-end machine learning pipelines for predictive modeling and statistical analysis. I enjoy extracting insights from complex datasets, then communicating them through clear visualizations and evidence-based experimentation.

In my projects, I built a Diabetic/Non-Diabetic Healthcare Predictor end-to-end—from data cleaning and feature engineering to model building, tuning, and comparison. I evaluated multiple classification algorithms and tuned the best-performing model to maximize accuracy and generalization.

I also developed a Book Rental Recommendation Engine using collaborative filtering (user-based and item-based) and evaluated predictions with RSME, improving project efficiency by 30%. For practical, business-relevant analysis, I ran Statistical Sales Analysis across TV, Radio, and Newspaper channels using web-scraped data, applying advanced statistical techniques and visualizing effect sizes.

Professionally, I’ve supported data integrity and reporting through operations roles—optimizing datasets with cleaning and preprocessing, coordinating and analyzing customer transaction data, and creating analytical reports that reduced customer queries by 5%. I’m motivated to take ownership, build from scratch to production when needed, and deliver reliable, decision-ready insights.