Snehal Patel — AI Researcher

I work at the intersection of data architecture and AI, focusing on building reliable, governed data foundations that make AI systems trustworthy and usable in real-world decision-making. For more than a decade, I’ve worked extensively with Centers for Medicare & Medicaid Services (CMS) provider data systems, including NPPES, PECOS, T-MSIS, QIES, POR, NCPDP, APS, MED, and PROVBX. These systems contain massive volumes of provider data across multiple source systems, each with different structures, quality levels, and completeness. My focus has been on structuring and integrating these sources into trusted data products. In large-scale Provider Master Data Management (MDM) initiatives, I’ve played a key role in designing the data structures and rules that feed identity resolution systems. This includes defining which provider attributes should be used for matching, which should be excluded to prevent false matches, how reference source data should be grouped and linked, and how data should be structured to support reliable identity resolution. I also designed NPI profile tables that generate golden provider records by combining data from multiple CMS reference systems. Because no single system contains complete information, the goal was to design structures and rules that assemble the most reliable attributes across sources. Engineering teams implemented these designs to produce trusted provider data profiles used across downstream data products. Beyond the technical work, I focus on aligning teams around clear data models, rules, and system behavior so complex systems can scale reliably. Currently, I’m leading an AI assistants initiative focused on building internal support agents. The first phase focuses on AI-powered helpdesk assistants capable of resolving Level-0 support requests using knowledge retrieval and structured documentation. This work reinforced an important lesson: successful AI systems depend far more on well-structured knowledge and retrieval architecture than on the model itself. I’m particularly interested in the future of AI-enabled data platforms, knowledge systems, retrieval architectures, and large-scale data governance. Outside of work, I’m a father of two energetic boys who keep life exciting. I enjoy exploring new places with my family and playing volleyball whenever I get the chance.

Stackforce AI infers this person is a Healthcare Data Architect with expertise in AI-driven data solutions.

Location: Mount Airy, Maryland, United States

Experience: 1 yr 1 mo