Python Developer

Introduction:

The candidate is a skilled software developer with a strong focus on AI, machine learning, and full-stack development. They have designed and implemented AI-driven models for demand forecasting, price prediction, and optimization in energy trading. With expertise in Python, VBA, and FastAPI, they have built end-to-end software solutions, integrating backend processing with user-friendly frontend deployment. Their experience includes developing robust data pipelines and automating workflows through RPA and custom scripts to improve efficiency. They have created sophisticated trading algorithms and predictive models for diverse sectors, including energy and finance. Additionally, the candidate has worked on developing dynamic web applications using Streamlit and has experience with cloud services and API integration. Their adaptability allows them to tackle a variety of challenges, from stock trading systems to business intelligence tools. They have a keen interest in leveraging their skills to solve problems across industries such as finance, sports, and beyond. The candidate’s focus on continuous learning and innovation, combined with a results-driven approach, enables them to create impactful solutions.

Responsibilities:

• Developed AI-driven models for demand forecasting, price prediction, and optimization in energy trading.
• Built scalable, production-level software using Python, integrating data processing, model training, and deployment.
• Created and maintained data pipelines using ETL processes to optimize workflows.
• Automated various business processes using VBA, RPA, and custom Python scripts.
• Architected and deployed end-to-end solutions for forecasting and automated trading systems.
• Developed and deployed dynamic web applications, including a stock trading bot using Alpaca API.
• Designed and implemented predictive models for photovoltaic energy production based on weather data.
• Integrated APIs for seamless data exchange and developed cloud-based solutions.
• Created automated reporting systems to reduce manual effort and improve efficiency.
• Built and deployed machine learning models for predictive analytics in energy and financial sectors.
• Developed systems for capacity use optimization and trading between multiple countries in energy markets.
• Worked with data visualization tools to present impactful insights and forecasts.
• Led the design of automated trading and forecasting ecosystems to support business decision-making.