Experience

I conducted extensive statistical analysis and time series forecasting on sales and inventory data, resulting in a 20% improvement in predictive model accuracy, which facilitated more informed decision-making regarding stock levels and promotions. I developed and implemented advanced anomaly detection algorithms to identify irregularities in sales patterns, reducing false positives by 25%, significantly enhancing system stability and ensuring data integrity. Additionally, I architected and deployed scalable machine learning models in Python using Scikit-learn, Pandas, and NumPy, resulting in a 30% reduction in model training and inference times for faster insights and actions. Utilizing advanced NLP techniques with PyTorch, TensorFlow, and Hugging Face Transformers, I enhanced text classification accuracy by 15%, facilitating real-time sentiment analysis that guided marketing strategies. I optimized data processing pipelines in Jupyter Notebook and Databricks using Pandas and PyArrow, achieving a 35% reduction in ETL processing times and improving overall data handling efficiency. Furthermore, I developed innovative prompt engineering strategies using LangChain, boosting AI-driven customer interactions by 20% and enhancing response accuracy in chatbot applications on the client’s website. Successfully deploying machine learning models on AWS cloud services, including SageMaker, Lambda, Glue, and EC2, I achieved a 40% increase in operational efficiency and a 50% reduction in deployment time across multiple environments, ensuring seamless integration into the client’s infrastructure.