Available to hire
I’m a GenAI and data science professional with 10+ years of experience designing and deploying AI/ML-powered solutions across finance, healthcare, retail, telecom, and banking. My work centers on building practical, scalable AI systems that solve real business problems while staying compliant with industry regulations. I’m passionate about turning complex data into clear, actionable insights and guiding teams through responsible AI adoption.
I specialize in Large Language Models, Retrieval-Augmented Generation, NLP, and multimodal AI, with hands-on experience in LangChain, Hugging Face, LlamaIndex, and OpenAI APIs. I’ve led enterprise-grade projects for credit risk, fraud detection, churn prediction, and personalized recommendations, and I’ve built robust MLOps/LLMOps pipelines across AWS, Azure, and GCP. I’m also focused on training and mentoring teams—135+ professionals—on prompt engineering and responsible AI practices to align AI initiatives with business outcomes.
Skills
Work Experience
Sr Generative AI Consultant at Voya Financial
April 1, 2024 - November 6, 2025Designed and deployed retrieval-augmented generation (RAG) pipelines with LangChain + Pinecone/FAISS, consolidating over 15M financial records and improving contextual retrieval accuracy by 30%, enabling faster and more compliant reporting. Fine-tuned LLMs (GPT-4, Claude, LLaMA2) using LoRA/QLoRA to generate synthetic borrower profiles and risk narratives, improving credit scoring accuracy by 22% and reducing underwriting delays. Integrated AWS Bedrock + LangGraph + MCP to orchestrate multi-agent workflows for explainable GenAI applications that passed security and compliance audits. Developed deep learning models for fraud detection and time-series forecasting, reducing false positives by 18%. Built real-time executive dashboards with Next.js + Streamlit, automated MLOps pipelines with Jenkins and SageMaker, and implemented comprehensive monitoring (Prometheus + Grafana) for drift and fairness. Led training sessions for 50+ employees on prompt engineering and responsible AI.
Sr Data Scientist/ GenAI Consultant at Walmart
March 1, 2024 - March 1, 2024Designed GenAI-driven personalization and fraud detection pipelines using LangChain, Hugging Face, and Azure AKS, boosting CTR by 18% and reducing fraud losses by 16%. Built semantic product search with LlamaIndex + Pinecone, enabling context-aware recommendations across millions of SKUs. Created GANs/VAEs for synthetic product imagery, cutting catalog prep time by 35%. Fine-tuned BERT/RoBERTa/GPT-3.5 embeddings for review summarization and fraud entity detection. Implemented real-time inference with Kafka + Spark Streaming for high-velocity transactions. Deployed ML services on Azure AKS via Docker; automated retraining with Airflow, MLflow, and dbt. Enabled cross-modal search with CLIP and observability dashboards (Prometheus + Grafana). Mentored teams on RAG design and Azure deployment, and exposed ML outputs via FastAPI/Flask APIs.
Sr Data Scientist at State of TX
August 1, 2022 - August 1, 2022Built predictive health models on Vertex AI, BigQuery, and Pub/Sub to forecast disease trends and optimize statewide resource allocation. Designed NLP pipelines for clinical notes and public health records, extracting topics and sentiment to guide prevention strategies. Leveraged Azure Databricks for scalable processing, developed Kibana X-Pack ML workflows for anomaly detection in admission rates, and created dashboards in Tableau/Power BI to visualize KPIs. Implemented HIPAA-compliant governance with encryption-at-rest and IAM-based access. Automated reporting pipelines and conducted workshops to drive adoption of AI-enabled dashboards.
Data Scientist at T-Mobile
September 1, 2018 - September 1, 2018Developed customer churn prediction and network optimization models using Scikit-learn, XGBoost, and TensorFlow. Built NLP pipelines on support transcripts for churn drivers and campaign optimization. Implemented real-time inference with Kafka + Spark Streaming for fraud detection and personalized experiences during peak periods. Deployed production ML services using Docker on Azure AKS; standardized retraining with Airflow, MLflow, and dbt. Enabled cross-modal search with CLIP for catalog navigation and built observability dashboards to reduce false positives and improve trust in AI outputs.
Python/ ETL Developer at Wells Fargo
September 1, 2018 - September 1, 2018Designed and optimized ETL pipelines using Python and SQL to support risk analytics and regulatory reporting. Built data validation and anomaly detection scripts, automated repetitive reporting, and delivered executive dashboards in Power BI/Tableau. Collaborated with governance teams to enforce standards and implemented predictive modeling on risk datasets. Enhanced query performance with tuned SQL and indexes, and contributed to monitoring and observability for critical financial workflows.
Data Analyst at Value Labs (Client: Wells Fargo), Hyderabad, India
June 1, 2016 - June 1, 2016Gathered requirements, performed data integration and profiling across SQL systems, and validated data quality for reporting pipelines. Built dashboards in Tableau/Power BI to provide KPIs and risk metrics, and supported data migration and new data marts. Automated reporting workflows and applied Scikit-learn models to risk datasets to derive actionable insights for compliance teams.
Education
Bachelor's in Business Administration at Osmania University, Hyderabad, India
January 11, 2030 - January 1, 2016Qualifications
Industry Experience
Financial Services, Healthcare, Retail, Telecommunications, Government
Skills
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