Svp, Senior Director Of Machine Learning & Data Platforms
CurrentResponsible for driving the technology, strategy, and execution of enterprise-scale data technologies and ML platforms to enable FactSet's AI initiatives. A key initial drafter and contributor to FactSet's GenAI investment Process in leveraging commercial and open-source LLMs and related tools to enable core AI objectives like text-summarization, internal chatbots, and most recently, personalization. Built FactSet's horizontal MLOps Team which enabled FactSet's first Enterprise-wide Machine Learning Platform and adoption of cutting edge ML tools for 1600+ engineers. This enables ~400 weekly active developers to accomplish at-scale capabilities that historically only specialized AI & ML engineers could accomplish. We enabled a firm-wide enterprise prompt repository, model catalog, self-service Vector databases as a platform and model governance. This led to not just leveraging commercial LLM Models like GPT-4 on Azure, Anthropic's Claude on AWS Bedrock but also enabled advanced GenAI workflows like RAG and fine-tuning of open-source models like Mistral, Llama2/3, and DBRX for our products.
