Owned and scaled AI data products, Resonate Embeddings and Segments, driving multi-million revenue and pipeline impact; expanded adoption across dozens of enterprise clients and hundreds of developers.
Embeddings: unlocked new DaaS/append revenue streams by enabling predictive vectors and semantic enrichment for enterprise analytics—generated seven-figure pipeline in the first months; delivered via Snowflake/Databricks/AWS and secure APIs.
Segments: enabled activation revenue by curating high‑intent, AI‑powered audiences for immediate activation in DSPs and programmatic channels—drove seven‑figure first‑year revenue and strengthened competitive differentiation.
Directed cross-functional pods (Engineering, Data Science, Data Engineering, MLOps, Analytics), providing indirect leadership to ~10–20 contributors; partnered with VP Product, VP Engineering, VP Data Science, GTM, Legal, and Privacy to align roadmap and execution.
Designed and initiated early architecture for an LLM‑powered audience discovery capability; established PRD, prototypes, and stakeholder alignment to compress audience build times from days to seconds across Finserv, Auto, Media, Retail, Travel, and Healthcare.
Modernized ML delivery and activation across Databricks, Snowflake, AWS, and clean rooms; standardized delivery formats, SDKs, and documentation to cut integration cycles by ~40%.
Improved platform performance and reliability with telemetry and ingestion observability; achieved double‑digit latency gains, including ~15% API latency reduction (REST vs gRPC) and ~30% ETL latency reduction via data pipeline optimization.
Established privacy‑first workflows aligned to clean‑room and CCPA requirements; partnered with Legal/Privacy to deliver compliant, ML‑ready datasets and secure activation pipelines (TLS, REST vs gRPC).
Recognition: Hackathon Winner — Most Innovative AI Product (2023); Hackathon Lead (2024) for embeddings visualization to improve model explainability and adoption.
