Bloomberg

Our Team:

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.

We partner closely with News Product and Engineering to elevate the performance of News Classification 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.

What’s The Role:
As a Data Product Owner, you will leverage subject matter expertise in financial news classification, annotation management, and process improvement to accelerate automation in our rule-creation workflow. You will play a crucial role, in collaboration with product and engineering teams, in developing scalable strategies for classification across news products, to drive continuous improvements for these systems. You will be accountable for delivering quantifiable, reusable improvements to enable our systems to meet the current and emerging needs of Bloomberg clients, align with internal product goals, and adhere to high standards of quality, transparency, and usability.

This role requires a strategic mindset and the ability to align data strategies with product objectives.

We’ll Trust You To:

• Apply strong financial news judgement to guide the hierarchical logic that automatically classifies Bloomberg and third-party news.
• Create the strategy and roadmap for developing technology-assisted processes to augment rule creation and modification
• Develop scalable frameworks for topic, entity and people classification across news products
• Define rule-development and annotation methodologies for news and social media content across multiple domains, partnering with engineers and product stakeholders to ensure alignment with market-specific nuances, end-user expectations, Bloomberg’s domain strategy, and overall product goals.
• Lead efforts to improve classification throughput, coverage, and enrichment scope by identifying automation and optimization opportunities.
• Leverage insights and analytics to measure the downstream impact of team initiatives on news products.
• Apply problem-solving and critical thinking, with a focus on innovation and continuous improvement to our news classification taggers.
• Stay current on trends in news classification, language models, search technologies, automated code development, and best practices in taxonomy management.

You’ll Need to Have:

• 4+ years of professional experience in the financial services or financial news industries, with strong judgment on financial news context and salience.
• Proven experience developing data annotation programs, rule-creation methodologies, and human-in-the-loop processes for AI/NLP products.
• Strong understanding of news classification with demonstrated experience managing hierarchical logic and taxonomies, for topic, entity and people tagging at scale.
• The ability to define a clear data product vision, build scalable roadmaps, and apply a strong analytical mindset to drive data quality and measurable business outcomes.
• Practical experience with search infrastructure, classification, and summarization models, specifically understanding how data quality influences relevance ranking and response generation.
• Excellent stakeholder management and project leadership skills, with a proven ability to evaluate design trade-offs and seamlessly translate technical complexities between Engineering, Product, and Data teams.
• Proficiency in leveraging analytics and visualization tools (e.g., Tableau, QlikSense, PowerBI) to track continuous improvements, measure downstream impacts, and identify automation opportunities.

We’d Love to See:

• Knowledge of Python, SQL, and common ML/NLP tooling.
• Experience working with annotation tools or platforms (e.g., Prodigy, Labelbox, Snorkel, etc.).
• Experience using native language skills to capture various forms of linguistic expression with high accuracy
• Experience with sophisticated data annotation initiatives at significant scale
• Background in information retrieval, semantic search, or abstractive summarization.
• Experience in data management concepts such as data quality, data modeling, and data engineering
• Experience customizing or developing annotation interfaces using Javascript or HTML.
• Certification in data governance (e.g., DAMA CDMP, DCAM).