Senior Data Management Professional - Data Product Owner - Annotation Management and Dialogue Labeling - London

- Own the end-to-end Annotation Lifecycle, from schema development to annotation execution, with a focus on ML performance and product utility. - Bridge the gap between finance and AI/ML by mastering domain-specific concepts that elevate communications experiences. - Design and manage annotation programs for search and summarization use cases, including training data for relevance ranking, query-document matching, and text abstraction. - Develop scalable strategies for data labeling and dialogue annotation, tailored for NLP enrichments across communication products. - Shape and evolve schematic structures and data models that serve as the foundation for annotation quality and reuse. - Define metadata structures and enrichment tags that help interpret communication context, intent, and relevance to user queries. - Collaborate with ML engineers and product stakeholders to align annotation efforts with model requirements and product goals. - Drive quality and consistency across annotation processes by developing clear guidelines, validation metrics, and governance frameworks. - Leverage insights and analytics to iterate on annotation strategies and measure downstream model and product impact. - Lead efforts to improve annotation throughput, coverage, and enrichment scope by identifying automation and optimization opportunities. - Stay current on trends in search technologies, summarization architectures, and best practices for building reliable training datasets in these domains. - Serve as a domain expert in data structuring, labeling, and ML data design within communications-focused NLP use cases. ###