V

Venugopal Reddy

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Illinois, United States

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Jobs verified_user 0% verified
  • Liberty Mutual
    GenAI Engineer
    Liberty Mutual
    May 2024 - Current (2 years 4 months)
    Designed multi-agent GenAI workflows using Azure OpenAI, LangChain, LangGraph, and MCP, enabling Planner, Retriever, Reasoning, and Compliance agents and improving task-resolution reliability by 14% across coverage-analysis scenarios. Built a production RAG pipeline with Azure Cognitive Search (BM25 + vector), FAISS, and ChromaDB to retrieve policy clauses, endorsements, and prior-claim data, improving retrieval quality on internal evaluation sets. Developed loss-summary generation modules using GPT-40 and LangGraph to extract structured facts from accident statements, repair estimates, adjuster notes, and subrogation documents, enabling faster claim-review cycles. Fine-tuned LLaMA and Mistral models with LoRA/QLoRA on de-identified insuran
  • HCSC
    Senior Data Scientist / Gen AI Engineer
    HCSC
    Jan 2022 - May 2024 (2 years 5 months)
    Developed clinical risk prediction models using XGBoost, LightGBM, and deep neural networks for readmission and disease-progression forecasting, improving targeting accuracy by approximately 25% on internal evaluation datasets. Implemented GenAI-driven clinical summarization pipelines using Amazon Bedrock, LangChain, and retrieval-enhanced prompting, enabling clinicians to review multi-encounter patient histories more efficiently during pilot testing. Built RAG workflows with FAISS, Amazon OpenSearch, and sliding-window + semantic chunking strategies to retrieve medical guidelines, coverage rules, and care protocols while maintaining HIPAA-compliant access controls. Engineered NLP extraction pipelines with BioClinicalBERT, spaCy, and custom
  • Bank of America
    Data Scientist / AI ML Engineer
    Bank of America
    Mar 2019 - Jan 2022 (2 years 11 months)
    As a Data Scientist / AI ML Engineer, I engineered fraud detection and anomaly-scoring models using XGBoost, LightGBM, and deep autoencoders to analyze high-velocity card transactions, successfully reducing false positives by 17% and accelerating fraud case closure rates. I designed real-time ML scoring pipelines using Pub/Sub and Dataflow to process millions of transactions per minute, delivering sub-second fraud alerts for card, ACH, and digital payment channels. Additionally, I built NLP pipelines using BERT, spaCy, and TF-IDF to extract entities and categorize SAR narratives, KYC documents, and investigator notes, which reduced AML review time by 35% and improved triage accuracy. I prototyped graph-based fraud features using NetworkX an
  • Safeway
    Data Scientist
    Safeway
    Aug 2017 - Jan 2019 (1 year 6 months)
    Developed demand forecasting models using ARIMA, Prophet, and Gradient Boosting to predict weekly SKU-level sales across 1K+ stores, reducing forecast error (MAPE) by 22% and improving replenishment accuracy for high-velocity items. Engineered inventory optimization models leveraging historical sales, vendor lead times, and seasonality indicators, helping supply chain teams cut stockouts by 18% during promotional cycles. Built and automated feature engineering pipelines in Python and PySpark on AWS EMR, creating lag features, holiday sensitivity curves, and weather-based demand modifiers that improved model performance across perishables and non-perishables. Designed price elasticity and promotional uplift models using scikit-learn and XGBo
  • F
    Python Developer
    FuGenX Technologies
    Jan 2015 - Jun 2017 (2 years 6 months)
    Developed Python-based data processing pipelines using pandas and custom parsers to clean, merge, and transform gameplay telemetry and mobile app logs, improving data readiness and reducing manual prep time by 45%. Built RESTful APIs in Flask to deliver gameplay insights, engagement metrics, and player behavior stats, reducing reporting turnaround time from days to minutes. Implemented automated ETL workflows using Python + cron and SQL procedures to ingest user events from MySQL/Oracle into analytics tables, improving daily KPI data availability. Engineered early ML prototypes (churn prediction, session drop-off detection) using scikit-learn, helping product teams identify retention risks ahead of new game releases. Created log-analysis sc
Education verified_user 0% verified
  • Gitam University
    Bachelor of Technology in Computer Science
    Gitam University
    Jan 2015 - Jun 2017 (2 years 6 months)
    Hyderabad