Ramteja V

About Ramteja V

I am a Senior Data Scientist with 11+ years of experience designing and deploying end-to-end AI and ML solutions that deliver measurable business impact across finance, healthcare, retail, SaaS, and government sectors.Over the past decade, I’ve advanced from hands-on ML engineering into enterprise AI leadership, driving adoption of Generative AI, Retrieval-Augmented Generation (RAG), and multimodal agentic systems. My expertise lies in bridging technical depth with business strategy — helping organizations reduce fraud losses, optimize clinical outcomes, and unlock operational efficiencies through data-driven intelligence.Generative AI & LLMs – Designed and deployed LLM-powered assistants, chatbots, and RAG pipelines using GPT, LLaMA, Hugging Face, LangChain, and vector databases (Pinecone, FAISS, Weaviate, Qdrant). Hands-on with multi-agent orchestration (LangGraph, CrewAI, AutoGen) and cost-optimized LLMOps (quantization, distillation, distributed training).Machine Learning & Deep Learning – Built fraud detection, credit risk, churn prediction, and clinical forecasting models using Random Forest, XGBoost, CNNs, LSTMs, Transformers. Applied explainable AI (SHAP, LIME) to meet strict regulatory requirements (FCRA, Basel HIPAA, GDPR).Big Data & Cloud AI – Scaled pipelines on AWS (SageMaker, Glue, Redshift), Azure (Synapse, Databricks), GCP (Vertex AI, BigQuery), processing billions of records via Spark, PySpark, Kafka, Airflow.MLOps & AI Governance – Implemented CI/CD pipelines, model monitoring (MLflow, Prometheus, Evidently AI, TruLens), and enterprise AI governance frameworks ensuring compliance, transparency, and ethical adoption.Leadership & Strategy – Led and mentored teams of 6–10 data scientists, influenced C-suite decision-making with ROI-driven AI insights, and secured $15M+ in budget approvals for AI expansion programs.I’m passionate about pushing the boundaries of Generative AI, multimodal intelligence, and scalable ML systems, while ensuring that AI remains ethical, explainable, and cost-efficient.

Experience

1. Senior Data Scientist

   Northwestern Mutual

   Feb 2023 — Present · Franklin, WI, US

   I lead the design and deployment of AI and Generative AI solutions focused on fraud detection, credit risk, and compliance analytics. I’ve built and productionized RAG pipelines using LangChain, Pinecone, Hugging Face, and FAISS, enabling investigators to query complex policy and transaction data in natural language and reducing case resolution time by 40%. I fine-tuned LLMs such as GPT, LLaMA, and BERT on domain-specific datasets with advanced prompt engineering to improve model accuracy and minimize hallucinations. My work includes developing real-time fraud detection systems with PySpark, Kafka, and LSTMs—cutting false positives and flagging 90%+ high-risk transactions. I automated KYC and loan document processing using NLP, built scalable ETL pipelines with Airflow, Spark, and AWS Glue, and migrated analytics workloads to Redshift and Snowflake, improving query performance threefold. I deployed containerized ML models using Docker, Kubernetes, and MLflow with CI/CD pipelines in AWS SageMaker, integrated Explainable AI (SHAP, LIME) for governance, and implemented model monitoring with Evidently AI and Grafana. These initiatives collectively delivered measurable outcomes—40% faster fraud investigations, 18% fewer loan defaults, and 12% higher client retention—while mentoring a team of data scientists and driving enterprise adoption of MLOps and LLMOps best practices.