Junior Data Scientist (Intern)
Avaada Energy Private Limited
Noida
09.2023 - Current
- Solar Power Plant Generation Prediction Model using LSTM CNN: Developed an advanced predictive model using LSTM (Long Short-Term Memory) and CNN (Convolutional Neural Network) architectures to forecast solar power generation. Integrated LSTM to capture temporal dependencies and CNN for feature extraction from time-series data. This model effectively utilized historical weather conditions, solar irradiance, and time-of-day information to predict solar power generation with high accuracy.
- Automated Module Performance, Daily Generation, and Robot Running Status Reports: Initiated a transformative process by developing and implementing automated solutions using Python for previously manual tasks involving the creation of Module Performance, Daily Generation, and Robot Running Status Reports. By leveraging Python programming, I designed efficient and automated data pipelines that retrieve, process, and transform raw data, eliminating manual data entry and significantly reducing processing time. Integrated Power BI for intuitive data visualization, generating comprehensive and interactive reports that provide stakeholders with actionable insights. This initiative streamlined reporting workflows, enhanced accuracy, and enabled real-time monitoring of module performance, daily generation trends, and robot operations.
- Developed Python-Tkinter GUI for Centralized Operations: Implemented a user-friendly Graphical User Interface (GUI) using Python's Tkinter library, consolidating essential functionalities in a single platform for seamless team usage. The GUI facilitated various operations such as prediction generation, file updating, and data exporting, streamlining team workflows and enhancing efficiency. Through thoughtful design and intuitive features, the Tkinter-based application offered a centralized hub for easy access to critical tasks. Users were empowered to perform predictions, update files, and export data seamlessly within one unified interface, minimizing the need to navigate through multiple applications or tools. This initiative not only simplified processes but also contributed to improved productivity and user experience by providing a cohesive environment for diverse operations.
