Predictive Analytics is the art and science of leveraging advanced machine learning algorithms to turn raw data into actionable foresight. My expertise lies in crafting sophisticated models that analyze historical data to uncover hidden patterns, predict customer behavior, and optimize business strategies. From forecasting sales trends to assessing risks, I empower businesses to stay ahead of the curve with precise, data-driven decisions.

I work with a variety of industries—retail, telecom, finance, and more—to deliver tailored solutions. For example, I can build a model to predict customer churn by analyzing usage patterns, demographics, and transaction history, enabling proactive retention strategies. Alternatively, I can forecast inventory needs based on seasonal trends and market shifts, reducing waste and boosting efficiency. My approach combines statistical techniques like time series analysis with cutting-edge deep learning methods to ensure accuracy and scalability.

Tools Used: Python, Scikit-learn, TensorFlow, Pandas, NumPy, Statsmodels

Applications: Sales forecasting, customer retention, market trend analysis, risk assessment, demand planning