Abhijeet Kartikeya

Machine Learning and Data Engineering professional with experience developing production-oriented ML systems for solar power forecasting and energy optimization. Skilled in time-series modeling, feature engineering, and deploying real-time prediction pipelines using Python and FastAPI. Experienced with Scikit-learn, TensorFlow, and modern GenAI frameworks including RAG and LangChain. Passionate about leveraging data to drive business decisions and scalable solutions.

ML/Data Intern at Tata Power Trading Company Ltd. (2026-02 – 2026-04)

Developed solar power forecasting system and ML models for power trading and grid load planning

• Developed solar power forecasting system by integrating multi-source weather APIs (irradiance, temperature, wind speed) using geo-coordinates, creating structured time-series dataset for model training.
• Engineered features and trained regression-based ML models (XGBoost/Random Forest), reducing forecast error (MAE) by ~12–15% compared to baseline estimation.
• Delivered day-ahead generation forecasts to support data-driven power trading and grid load planning decisions.

Intern at Central Bank of India, IT Department (2025-07 – 2025-09)

Automated reporting tasks and supported database operations in production systems

• Automated structured reporting tasks using Python, reducing processing time by ~25%.
• Supported SQL query validation, debugging, and database consistency checks in production systems.
• Assisted in system monitoring and issue resolution to maintain data integrity.

B.Tech in Computer Science – HMR Institute of Technology and Management (2022 – 2026)