Data Science Intern
• Leveraged statistical and machine learning models for time-series forecasting in Python to forecast KPIs essential to business operations, enhancing revenue forecast accuracy by 10%.• Streamlined the data loading process of POS data in the forecasting pipeline by using SQL to aggregate and analyze traffic data, enabling more timely and accurate forecasting insights.• Developed interactive dashboards with backtest visuals in Tableau to enhance data-driven decision-making for senior leadership.• Supported the application of hierarchical forecasting techniques to enhance the team’s forecasting process.• Competed in a Nike business challenge, proposing a new venture, creating a business plan, and presenting to over 200 people and a panel of judges.