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AI Engineer with 3+ years in Machine Learning & Predictive Analytics
Data Scientist and AI Engineer with a background in UI/UX Design, combining user-centered design thinking with deep expertise in machine learning, predictive analytics, and power trading forecasting. Proficient in Python, SQL, statistical modeling, and data visualization with hands-on experience in time-series forecasting, demand prediction, experimental design, and business intelligence. Adept at building end-to-end ML pipelines from data ingestion and feature engineering to model deployment with Flask and Docker and translating complex datasets into actionable insights that drive operational efficiency and product performance.
Paavai Institutions
Bachelor of Technology · Information Technology
N/A – June 30, 2021
Freelance
UI/UX Designer
January 1, 2025 – Present
India
Dappl India Private Limited
Senior UI/UX Designer
June 1, 2022 – December 1, 2024
Chennai, Tamil Nadu, India
Power Trading Demand Forecasting
May 14, 2026 – Present
Built an end-to-end machine learning pipeline for short-term electricity demand and price forecasting using XGBoost ensemble models with recursive forecasting, achieving 94% forecast accuracy across 15 power trading zones. Engineered 40+ advanced time-series features (lag variables, rolling statistics, calendar effects, weather signals) from 500K+ records spanning 3+ years, significantly improving model predictive performance. Developed an automated data ingestion and preprocessing pipeline using Python and SQL to integrate market signals, grid load data, and external weather APIs, reducing data preparation time by 65%. Achieved 8% MAPE (target <10%), reducing error by 18% vs. baseline ARIMA models through robust feature engineering and hyperparameter tuning. Deployed scalable forecasting services as REST APIs using Flask and Docker, enabling real-time inference for power trading and dispatch decisions. Integrated Prometheus for real-time metrics collection (inference latency, request throughput, model performance) and built Grafana dashboards for system monitoring, alerting, and operational visibility. Designed and delivered an interactive Power BI dashboard to visualize forecast vs. actual demand, price volatility trends, and zone-level KPIs, enabling data-driven decision-making. Implemented rigorous backtesting and cross-validation across multiple forecasting horizons to ensure model robustness, stability, and production reliability.
Diploma in Professional Data Science and Artificial Intelligence
AiSpry
January 1, 2026 – Present