Jahnavi P

• Perfected machine learning models, including neural networks and time series analysis, to forecast demand accurately. Expanded and refined datasets to improve predictions for inventory optimization.

• Led data cleaning and normalization efforts (using log scaler, robust scaler, etc.), and performed feature engineering to enhance model reliability.

• Employed advanced visualization techniques to illustrate forecasted trends clearly, providing stakeholders with actionable insights for informed decision-making.

• Conducted detailed comparisons between forecasted and actual sales data, identifying opportunities for improving forecast accuracy and operational efficiency.

• Collaborated across functions to leverage predictive analytics in developing strategies that optimized inventory management and streamlined supply chain operations, contributing to organizational objectives.

• Leveraged Python and Excel to analyze large datasets, enhancing operational efficiency and customer service processes within the Customer Support team.

• Spearheaded analysis across various customer service channels using Tableau, conveyed insights to improve processes and reduce response times, significantly enhancing customer experience.

• Fostered cross-functional collaboration by integrating data analysis with customer service operations, enhancing process efficiency, and automating data collection and analysis with Python scripts.

• Partnered with various departments to ensure data accuracy and integrity, bolstering the reliability of customer service insights, and supporting strategic decision-making.

• Utilized Python to analyze internal and external data sources, shaping key business strategies, influencing product development, and providing competitive insights that led to a strategic advantage.

• Conducted comprehensive evaluations of datasets to identify trends and actionable insights with Python, contributing to business growth and an increase in customer retention through informed decision-making.

• Generated standard and custom reports using Excel, summarizing critical business, financial, and economic data, which led to more efficient resource allocation and supported strategic planning.