Navya Devarinti

Develop production Python AI/ML applications and scalable ML pipelines using Python, Pandas, NumPy, SQL, PySpark, Azure Machine Learning, Azure OpenAI, Databricks, Snowflake, TensorFlow, and PyTorch. Build end-to-end workflows covering data preprocessing, feature engineering, model training, evaluation, validation, deployment support, monitoring, and operational analytics.

Developed production Python-based ML platforms and services using AWS SageMaker, Databricks, PySpark, Snowflake, TensorFlow, PyTorch, and Delta Lake. Engineered scalable data-processing, feature-engineering, and ML workflows using Python and Spark/PySpark for large-scale production workloads.

Developed enterprise Python AI/ML solutions using AWS SageMaker, Databricks, PySpark, Snowflake, TensorFlow, Azure OpenAI, and Delta Lake for healthcare risk, fraud, forecasting, and operational intelligence. Built Python/PySpark ML pipelines for data preprocessing, feature engineering, model development, evaluation, validation, and operational analytics.

Developed Python/PySpark ML platforms and scalable data-processing workflows using Spark, SQL Server, Oracle, Hadoop, and Snowflake for credit risk, fraud detection, and customer intelligence. Built predictive models using XGBoost, LightGBM, Random Forest, Gradient Boosting, TensorFlow, Spark MLlib, and ensemble methods.

Developed enterprise ML and data solutions using Python, Scikit-Learn, TensorFlow, NumPy, Pandas, SQL Server, MySQL, and Apache Spark for customer analytics, forecasting, recommendation, and intelligent automation. Built supervised-learning, anomaly-detection, and predictive-monitoring solutions and supported scalable data preparation and model development workflows.