Satyanarayana Repala — Data Scientist

I am a Senior Data Scientist with proven expertise in fraud detection, recommendation systems, generative AI, and large language models (LLMs). My experience spans finance, media, e-commerce, and technology, where I design and deploy AI solutions that deliver measurable business impact. At Morgan Stanley, I lead the development of account takeover (ATO) prevention systems, building advanced anomaly detection models, real-time detection features, and vendor integrations for identity verification and early warning signals. I also developed an LLM-powered fraud intelligence platform that surfaces emerging patterns and reduces analyst investigation time, while ensuring model governance and regulatory compliance. Previously at Condé Nast, I delivered measurable lifts in engagement by building graph-based recommendation systems, implemented retrieval-augmented generation (RAG) pipelines to enhance content discovery, and developed multimodal AI systems such as a CLIP-based image search engine that improved user engagement and product discoverability. I bring strong expertise in transformers, GNNs, autoencoders, RAG pipelines, time series forecasting, and statistical modeling, along with hands-on skills in Python, PyTorch, TensorFlow, Spark, and Databricks. Beyond building models, I focus on end-to-end deployment, monitoring, and governance, ensuring AI solutions are accurate, ethical, and scalable. I am passionate about Generative AI, LLM fine-tuning, and applied machine learning research, and I actively share knowledge through blogging and industry contributions

Stackforce AI infers this person is a Fintech and E-commerce expert specializing in AI-driven fraud detection and recommendation systems.

Location: Bengaluru, Karnataka, India

Experience: 9 yrs 9 mos