Senior Data Management Professional - Data Product Owner – Enterprise Data Agent

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem‑solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.

The Bloomberg Data AI group brings innovative AI technologies into Bloomberg’s Data organization while supplying deep financial domain expertise to the development of AI‑powered products. The Code Generation Data Team provides strategic data management solutions for AI/ML systems that perform code generation. We partner closely with cross functional team members to align AI innovation with Bloomberg’s strategic objectives, focusing on optimizing data workflows and elevating the quality, intelligence, and usability of the data that drives our products.

We are seeking a Data Product Owner to lead the evaluation, annotation, and data quality systems underpinning the Enterprise Data Agent. As Bloomberg expands its enterprise data offerings, enabling users to efficiently discover, understand, and interact with data is increasingly critical. The Enterprise Data Agent is a strategic product designed to improve how users explore datasets, surface insights, and interact with Bloomberg’s enterprise data commercial offerings through AI‑driven workflows. A key component of this product is ensuring that AI‑driven experiences are accurate, reliable, and continuously improving. This requires robust evaluation frameworks, high‑quality annotation systems, and measurable feedback loops.

This role goes beyond traditional product ownership as you will act as the owner of the evaluation data layer, responsible for ensuring that user interactions, feedback, and annotated datasets translate into high‑quality signals for model improvement and product performance. You will take ownership of fragmented, manual processes and transform them into scalable, repeatable, and measurable systems that support both human‑in‑the‑loop workflows and automated evaluation.

We’ll Trust You To:

• Own and scale evaluation and annotation workflows, transforming fragmented processes into reliable, high‑signal pipelines
• Define and operate a release evaluation framework, ensuring consistent, human‑validated signals on product and model quality
• Drive development of automated evaluation (auto‑eval) to improve scalability and reduce manual dependency
• Establish and manage error and theme taxonomies, enabling structured, actionable insights for product and engineering
• Translate user feedback and evaluation outputs into prioritized product improvements, partnering closely with Engineering and Product
• Define, track, and report on key performance metrics, ensuring transparency into data quality and product performance

You’ll Need To Have:

• 4+ years of experience in data product ownership, data operations, or AI/data evaluation workflows
• Strong understanding of data quality, data modeling, and AI evaluation methodologies
• Experience working with annotation workflows, labeled datasets, or human‑in‑the‑loop systems
• Proven ability to translate ambiguous problems into structured frameworks and processes
• Experience collaborating with engineering and product teams on AI/ML‑driven products
• Proficiency in SQL, Python, or similar tools for data analysis and validation
• Strong organizational and prioritization skills, with the ability to manage both strategic and operational responsibilities

We’d Love To See:

• Experience with search, retrieval, or agent‑based AI systems
• Familiarity with evaluation frameworks for generative AI or LLM‑based products
• Experience designing taxonomies, ontologies, or structured labeling systems
• Understanding of enterprise data products and user workflows
• Experience working with data discovery platforms or metadata systems
• Knowledge of Bloomberg Enterprise Data
• Experience in Agile/Scrum environments

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.