Ravi chandra sekhar User

I’m a Data Scientist focused on turning messy data into ML-driven decisions that move key metrics. I build end-to-end pipelines—from SQL-based data prep to model training, experiment analysis, and business-ready outputs.

At Eficens Systems (Client - H.E.B), I built an XGBoost churn prediction model for high-value retail segments, identifying at-risk users with a 0.76 F1 score. I integrated the results into automated retention workflows, delivering a 9% reduction in churn and an estimated $450K in annual revenue retained via targeted outreach.

I also designed and owned a weekly anomaly detection pipeline using SQL window functions and Python to monitor category-level conversion rate drops. This work eliminated ~15 hours/month of manual auditing and strengthened data quality oversight for stakeholders, while my statistical analysis supported multivariate pricing decisions using Welch’s t-tests and ANOVA.

Earlier at Flipkart (E-Commerce), I developed SQL and Python pipelines for category-level sales analysis during Big Billion Days, cutting average query time by 25% through a consolidated data model. I’ve run and analyzed A/B tests (e.g., improved click-to-conversion by 5%), forecast daily order volumes with Linear Regression (R² = 0.77), and communicated insights through EDA dashboards for product teams.