With a master's degree in statistics from Carnegie Mellon University and over three years of professional experience, I am a data scientist at E Source who specializes in predictive analytics and large-scale data engineering for the energy sector. I apply statistical analysis and machine learning algorithms to forecast demand, segment customers, and evaluate programs, using a blend of supervised and unsupervised learning techniques.My work has enabled data-driven decision-making and improved operational efficiency and planning for various clients in the energy industry. For example, I spearheaded a project that leveraged natural language processing to analyze survey data and demographic data, and identified key factors that influenced customer satisfaction and retention. I also built a time series analysis pipeline that incorporated hierarchy of new business projects across multiple levels of service. I am passionate about leveraging data to drive both economic and environmental benefits, and I would love to connect with you if you share these interests or have any questions.