Senior Data Scientist
CurrentProject 1: AWS cloud-based IDARE Automated Machine Learning web application (IdareAI)• Leading a cross-functional team to create an AI-based solution builder tool and perform predictive analytics.• Built pipelines to Extract, Transform, and Load (ETL) big data from different sources and production-ready end-to-end ML pipelines using Pandas, Scikit-Learn, and PyTorch.• Reduced project delivery time from 12 weeks to 4 weeks through automation.• Providing active support and online training to 500 subscribers• Award: Received an innovation research grant of $200,000 from the US Department of Energy (DoE).Project 2: Visualization and Streaming Sensor Data in Dashboards• Led the development of an AWS cloud-based custom dashboard application using MS SQL Server, MongoDB, Pandas, and Plotly to visualize complex data from IoT sensors.• Implemented ETL pipelines, interactive data filtering, and drill-down features, designed the user interface, enhancing user engagement, facilitating more in-depth analysis, dynamic reporting, and generating $1M/year in revenue.Project 3: Predicting Short-term Loan Default and Customer Churn for a Bank• Handled big data from 130 branches and extracted key details about microfinance operations.• Built a pipeline to predict loan defaulters and customer churn using AutoML, and saving $500k/year.• Created financial dashboards in Power BI to get daily and monthly summaries for decision support.Project 4: Electricity Net Load Forecasting• Created a robust production-level codebase for electricity net load forecasting using Prophet and XGBoost, catering to the needs of four distinct US utility companies.• Established a comprehensive MLOps pipeline to monitor the entire ML model lifecycle, including model development, deployment, and ongoing monitoring, enabling daily scheduled predictions to support operational decisions.