Naresh valleru

Delivered end-to-end AI/ML consulting solutions across 8+ enterprise clients in finance, government, and manufacturing, resulting in significant operational cost savings through intelligent automation. Built LLM-powered document intelligence pipelines using AWS Bedrock, BERT transformers, and OCR, processing over 100K documents per month with 95% accuracy in entity extraction and an 80% reduction

Developed robust data ingestion pipelines from disparate enterprise systems, integrating with Azure Data Factory, Event Hubs, and Databricks for downstream ML processing. Built and operationalized over 25 ML models for time-series forecasting, classification, and anomaly detection using Azure Databricks, boosting fraud detection accuracy by 30% and mitigating potential losses.

Led provisioning and administration of AWS EMR clusters managing over 200TB of government data, secured with RBAC and SAML, supporting 50+ federal agencies with 99.8% uptime. Designed and managed Spark-based ETL pipelines to ingest and process data from external APIs into PostgreSQL, MongoDB, and Redshift, improving ingestion reliability and reducing processing latency by 60%.

Configured and managed Hadoop components including Hive, Pig, HBase, and Oozie in a CDH environment. Migrated data pipelines to Cloudera distribution on AWS EC2 and Databricks.

Implemented data ingestion and processing solutions using Hive, Pig, Sqoop, and MapReduce. Developed Spark transformations using Scala and Python to optimize data processing and analytics.

Provided DataStage consulting services to the University of Florida. Focused on data integration and ETL processes.

Served as a DataStage Consultant for the Federal Deposit Insurance Corporation. Responsible for developing and maintaining data integration solutions.

Worked as a DataStage Developer at Nike. Involved in designing and implementing data extraction, transformation, and loading processes.

Obtained a Bachelor of Technology degree, building a strong foundation in engineering principles and practical applications. Developed core competencies through coursework and projects.

Completed a Master of Science degree, focusing on advanced topics and research within the field. Gained in-depth knowledge and specialized skills relevant to the industry.