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 technological solutions to enhance our systems, products, and processes, and provide support to our clients.

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 key focus areas supports compliance monitoring and supervision through structured annotation of electronic communications. These annotations underpin critical policy controls, model training, and enrichment pipelines that enhance compliance coverage, communication understanding, and risk detection.

Our team builds and manages scalable annotation frameworks and governance systems that help ensure compliant, high-quality datasets. We partner closely with Compliance, Product, and Engineering to design annotation guidelines, establish review and escalation protocols, and ensure alignment with evolving regulatory and internal policies.

What’s The Role:

As a member of the Query Enrichment team, you will help make Bloomberg’s GenAI capabilities smarter, faster, and more intuitive. Our work connects data science, natural language processing, and human judgment — enriching queries to ensure users receive the most accurate and relevant responses possible. We partner closely with other Data teams, as well as Product and Engineering to enhance the intelligence behind Bloomberg’s AI offering.

We’ll trust you to:

• Own and run key query enrichment initiatives, which are predominantly focused on annotation process management from build to execution. Contribute to the evolution of Bloomberg’s query enrichment processes by crafting scalable, quality-controlled annotation projects to train and evaluate LLM models and their output

• Applies technical acumen and product mindset to define and drive the strategic evolution of annotation projects, ensuring robust quality metrics are created and utilised to iterate on workflows and performance.

• Collaborate with partners to scope, evaluate, and refine data enrichment tasks. This includes creation of project guidelines, implementation of annotation protocols and providing relevant progress reports and feedback.

• Perform advanced business intelligence, metric analysis, and process automation.

• Develop and document reproducible analysis notebooks that clarify results and streamline stakeholder reporting.

You’ll need to have:

• At least 3 years of professional experience in information management, data analytics, or technical project coordination.

• Experience owning the end-to-end lifecycle of a data product, including design, delivery and measurement with a focus on ensuring data meets consumer needs and drives actionable outcomes.

• Ability to translate technical metrics into business insights for product stakeholders.

• Excellent problem-solving and analytical thinking skills with strong attention to detail.

• Proven track record of stakeholder relationship management, communication, and cross-team collaboration.

We’d love to see:

• Strong proficiency in Python (Pandas, NumPy, and data visualization libraries).

• Experience developing or managing annotation programs and training/evaluation datasets for ML or NLP models.

• Basic understanding of HTML, CSS, and JavaScript for maintaining task-presenter tools.

• Prior involvement with distributed data labeling operations.