Data Science Associate
Current• Analyzed 370000+ energy data on residential and commercial buildings to segment marketing opportunities using Python NumPy and Pandas libraries.• Redesigned existing Power BI dashboard for core environmental KPIs (greenhouse gas emission (GHG) and energy cost reduction).• Employed gradient boosting and clustering algorithms using Python XGBoost and scikit-learn libraries to generate new predictive models for retrofit pathway recommendation engine.• Collaborated with engineers and software developers to deploy predictive models developed in Azure ML Studios into production.