Pooja Telavane

-Conducted exploratory data analysis (EDA) utilizing Pandas and advanced Excel techniques. -Boosted productivity by automating data manipulation processes with Python, resulting in an average time saving of 5 hours per week. -Familiarity with best practices in data science and applied forecasting methodologies. -Expertise in feature engineering techniques to enhance forecasting accuracy and model robustness.

-Achieved a 15% enhancement in model accuracy by refining feature engineering and fine-tuning hyper parameters. -Extracted valuable insights from a dataset comprising 100,000 customer survey responses, resulting in a 20% increase in customer satisfaction. -Led initiatives to professionalize the data science workflow, including requirements gathering, modeling, evaluation, and productiondeployment.