Paril Ghori is a results-driven data scientist with a proven track record in machine learning, deep learning, NLP and MLOps, specializing in financial analytics, anomaly detection and predictive modeling. With expertise in Apache Spark, PyTorch, TensorFlow and cloud computing, Paril has built anomaly detection models that saved thousands of manual hours and identified financial anomalies worth millions of dollars. He has also spearheaded the development of AI-powered sentiment analysis for earnings call transcripts, helping businesses understand market impact on stock prices. Beyond modeling, Paril has optimized MLOps pipelines, automated cloud-based analytics and developed scalable anomaly detection frameworks. His work on NLP-driven customer insights and marketing mix models has increased ROI and operational efficiency. Passionate about innovation, Paril thrives at the intersection of AI, cloud computing and business intelligence, continuously pushing the boundaries of data science to create real-world impact.