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 (AWS, Databricks, Azure), Paril has delivered impactful AI solutions that drive business efficiency and innovation.

Paril has built anomaly detection models that saved thousands of manual hours and identified financial anomalies worth millions of dollars. His predictive modeling expertise has led to an 80% accurate business lead forecasting system, empowering organizations to make data-driven strategic decisions. 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 to support multiple business cases. His work on NLP-driven customer insights and marketing mix models has directly 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.