Data Scientist with experience building and deploying production grade Generative AI and machine learning systems in regulated banking environments. Strong background in LLM based architectures, Graph RAG, deep learning,…
Data Scientist with experience building and deploying production grade Generative AI and machine learning systems in regulated banking environments. Strong background in LLM based architectures, Graph RAG, deep learning, and cloud platforms including AWS and Azure, focused on designing scalable, auditable AI systems that improve compliance, decision making, operational efficiency, and drive measurable cost reduction.
Built a GPT-5-Chat and Graph-RAG powered policy comparison platform on Azure AI Search, processing 400+ regulatory and internal policy documents and automating compliance gap detection, reducing manual review time by 600%, lowering legal and compliance risk across multiple business units.
Productionized multi-agent generative AI macroeconomic reporting and reasoning system deployed on AWS, transforming unstructured financial data into 60+ computed indicators.
Integrated Claude Sonnet 4.5 with agent layers for reasoning and trend forecasting, enabling real-time executive dashboards with 100x faster insight generation.
Delivered an AML fraud detection system for 18M+ customers using behavioral and demographic modeling and alert optimization, reducing undetected fraud to 0.5% and strengthening regulatory compliance.
Built a GPT-5-Chat and Graph-RAG powered policy comparison platform on Azure AI Search, processing 400+ regulatory and internal policy documents and automating compliance gap detection, reducing manual review time by 600%, lowering legal and compliance risk across multiple business units., Productionized multi-agent generative AI macroeconomic reporting and reasoning system deployed on AWS, transforming unstructured financial data into 60+ computed indicators. Integrated Claude Sonnet 4.5 with agent layers for reasoning and trend forecasting, enabling real-time executive dashboards with 100x faster insight generation., Delivered an AML fraud detection system for 18M+ customers using behavioral and demographic modeling and alert optimization, reducing undetected fraud to 0.5% and strengthening regulatory compliance.
Architected a GenAI framework on AWS, where web scrapers and a Model Context Protocol (MCP) pipeline work together to ingest macroeconomic data.
Used insight generation layer to produce automated analytical reports.
Applied advanced network graph analytics using role-based modeling to identify high-risk network clusters.
Performed community detection using modularity-based Louvain Algorithm to uncover 1.7M+ previously un-flagged illicit activities.
Architected a GenAI framework on AWS, where web scrapers and a Model Context Protocol (MCP) pipeline work together to ingest macroeconomic data. Used insight generation layer to produce automated analytical reports., Applied advanced network graph analytics using role-based modeling to identify high-risk network clusters. Performed community detection using modularity-based Louvain Algorithm to uncover 1.7M+ previously un-flagged illicit activities.
Built React PCF components in TypeScript integrated with Power Apps.
Designed configurable UI workflows that allow low code users to generate and execute SQL queries without manual coding.
Built React PCF components in TypeScript integrated with Power Apps, designing configurable UI workflows that allow low code users to generate and execute SQL queries without manual coding.
Orchestrated a XAI-based detection system using ultrasound images and clinical data, leveraging CNNs and ma chine learning models. Applied SHAP, LIME, and Grad-CAM for explainability, and integrated vision language model (VLM) to generate context-aware textual explanations.
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