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 innovative workflow efficiencies, and we implement technology solutions to improve our systems, products and processes - all while providing customer support to our clients.

Our Team:

The Bloomberg Data AI group brings cutting-edge AI technologies into Bloomberg’s Data organization while contributing deep financial subject matter expertise to the development of AI-powered products. We partner closely with stakeholders 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. Our work amplifies the impact of the Data organization by delivering intelligent data solutions and domain-informed systems that improve the capabilities and competitiveness of Bloomberg’s offerings.

What's the Role?

As the scale and strategic importance of AI-powered products at Bloomberg continues to grow, we are seeking a strategic leader to oversee the teams responsible for producing high-quality training and evaluation data that power Bloomberg’s structured intelligence systems.

This organization plays a foundational role in ensuring that structured representations used by Bloomberg’s AI systems are accurately modeled, consistently annotated, and rigorously evaluated. The role is responsible for defining standards for intent modeling, schema alignment, annotation quality, and evaluation methodologies, ensuring precision, consistency, and domain fidelity across structured AI workflows.

You will establish scalable production practices and governance frameworks that enable structured training and evaluation data to evolve alongside increasingly sophisticated AI models. A key part of this mandate is strengthening technical fluency across the organization, elevating how teams design structured representations, reason about evaluation rigor, and ensure data integrity in support of reliable model performance.

Working closely with Product, Engineering, and the CTO’s Office, you will align structured data artifacts with both business priorities and technical requirements, ensuring Bloomberg’s AI systems are grounded in well-designed, well-evaluated, and high-quality structured intelligence.

Join a team shaping the quality, rigor, and long-term impact of the structured intelligence layer powering Bloomberg’s next generation of AI-driven products.

We’ll trust you to:

• Lead and scale a technically fluent organization responsible for producing high-quality training and evaluation datasets that power Bloomberg’s structured AI systems, while hiring, mentoring, and developing the next generation of technical leaders.

• Establish clear standards, governance frameworks, and performance metrics to ensure consistent, high-quality data production at scale.

• Partner closely with Engineering, Product, and AI stakeholders to align data design and evaluation methodologies with modeling approaches and production requirements.

• Guide teams in translating complex financial expertise into precise, high-fidelity structured representations suitable for advanced AI applications.

• Drive improvements in tooling, automation, and operational workflows to increase data quality, scalability, and organizational leverage.

• Operate as a strategic leader, balancing near-term delivery with long-term capability building and platform maturity.

You’ll need to have:

• 8+ years of experience leading AI/ML data, annotation, or evaluation organizations, including significant people leadership responsibility.

• Demonstrated success building and operating large-scale data production functions that support machine learning systems in production environments.

• Strong technical fluency, with the ability to engage credibly with engineering and AI partners on how data design, structure, and quality influence model behavior and system performance.

• Deep understanding of generative AI workflows and the role rigorous training and evaluation data play in ensuring reliability and domain accuracy.

• Proven ability to develop technical talent and elevate team sophistication in structured data design and evaluation practices.

• Strong analytical judgment and leadership presence, with the ability to balance long-term strategy and near-term execution while communicating complex ideas clearly across stakeholders.

We’d love to see:

• Advanced degree in Computer Science, Engineering, Data Science, or a related field.

• Experience operating in highly technical, ML-adjacent, or data-intensive environments.

• Background in financial services or similarly complex, domain-rich industries.

• Familiarity with modern annotation platforms, data tooling, and quality systems.

• Prior hands-on experience in technical or engineering contexts.