Senior Data Management Professional - Data Annotation Operations and Quality

Senior Data Management Professional - Data Annotation Operations and Quality

Location

Skillman

Business Area

Data

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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, implement technology‑driven solutions to enhance our systems, products, and processes, and provide support to our clients.

The Bloomberg Data AI group brings cutting‑edge AI technologies into Bloomberg’s Data organization, supplying deep domain expertise to the development of AI‑powered products. One of our core areas focuses on News Content Indexing, supporting Natural Language Processing (NLP) enrichments across multiple news platforms. These enrichments are critical for managing the automated classification of the world’s most meaningful financial and economic news, with the aim of further entrenching Bloomberg as the leader in the financial news market.

Our team builds and manages scalable annotation frameworks, driving quality training and evaluation datasets. We partner closely with News Product and Engineering to elevate the performance of Machine Learning (ML) models, enrichments, and features delivered to clients. Looking forward, our roadmap includes the expansion of our coverage universe and support of further enhancements to Bloomberg’s News summarization offerings.

A Senior Data Management Professional (DMP) is a key role within our organization responsible for providing subject matter expertise in both financial concepts and annotation program management, to the development of our AI products. These individuals act as proactive technical leaders by setting the framework in achieving quality and consistency in the evaluation and training datasets for models that power our AI‑enhanced products, and delivering scalable governance in annotation program management across Bloomberg Data.

Beyond governing data processes and being problem solvers, they are expected to transform the responsibilities of the team and scale the impact beyond what’s possible today.

This role requires a strategic mindset around ML training data design, a strong understanding of data modeling and schema architecture, and the ability to align data strategies with product objectives. You will also be responsible for designing data pipelines and annotation schemas that support search relevance modeling, text summarization, and classification enrichments, enabling fast, relevant, and trustworthy information delivery. You’ll be expected to guide the data design that supports identifying salient content, and generating concise responses or insights that drive decision‑making for Bloomberg clients.

You may also be responsible for providing support for our NLP solutions in other domains involving complex financial instruments.

• Own the end‑to‑end Annotation Lifecycle, from schema development to annotation execution, with an eye toward ML performance and product utility.
• Apply problem‑solving and critical thinking, with a focus on innovation and continuous improvement to our news classification taggers.
• Design and manage annotation programs for news enrichments.
• Develop scalable strategies for topic and entity classification, tailored for NLP enrichments across news products.
• Shape and evolve schematic structures and data models that serve as the foundation for annotation quality and reuse.
• Incorporate machine learning and statistics to detect anomalies and drive quality improvement in areas such as accuracy, completeness, consistency, and reliability.
• Collaborate with AI 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…