Senior Data Management Professional - Equity Corporate Actions Data
Bloomberg
Data Science
London, UK
Posted on May 18, 2026
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.
Our Team:
Our Equity Corporate Actions Data team underpins Bloomberg’s Terminal and enterprise services by sourcing, validating, and publishing accurate equity reference and corporate-actions information, from distributions, to mergers & acquisitions, stock splits, spin-offs, and beyond, to hundreds of thousands of users worldwide.
What’s the role?
We are looking for a Senior Data Management Professional to help scale and govern AI-driven and automated data workflows across Equity Corporate Actions and Reference Data products. This role focuses on ensuring that automation systems — including rule-based pipelines, intelligent document processing, and LLM-driven workflows — produce accurate, measurable, and operationally resilient outputs at scale.
You will help define how we evaluate, monitor, and continuously improve automated data processing systems by designing quality measurement frameworks, production monitoring capabilities, and human-in-the-loop governance processes. The role sits at the intersection of financial domain expertise, data quality management, and AI-enabled operations.
As our automation footprint expands, this role will play a critical part in ensuring our datasets remain trusted, explainable, and fit-for-purpose for Terminal, Enterprise, and AI-driven downstream products.
We’ll trust you to:
- Define and implement quality assurance frameworks for AI-driven and automated data processing systems
- Design operational metrics to measure automation accuracy, timeliness, completeness and downstream data quality impact
- Monitor production AI workflows for degradation, drift, inconsistencies, and systemic quality risks
- Develop methodologies for human-in-the-loop review and escalation processes
- Partner with Engineering teams to improve automation reliability and observability
- Conduct root-cause analysis across automated workflows and identify structural remediation opportunities
- Evaluate tradeoffs between automation coverage, operational scalability, and data quality outcomes
- Help establish standards for prompt management, evaluation testing, and deployment governance for LLM-enabled workflows
- Build dashboards and analytical tooling to monitor automation effectiveness and quality trends over time
You’ll need to have:
- A BA/BS degree or higher in Computer Science, Mathematics, Finance or relevant data technology field, or equivalent professional work experience
- 4+ years’ experience in data analysis, financial market research, and/or information technology
- Sound understanding of data quality as a domain of data management (DAMA CDMP, DCAM certification a plus)
- Experience monitoring or evaluating automated, AI-assisted, or machine learning-driven workflows in production environments
- Ability to investigate ambiguous or probabilistic system behavior and translate findings into operational improvements
- Analytical and data profiling skills using Python and SQL
*Please note: years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
We’d love to see:
- Familiarity with LLMs, intelligent document processing, NLP systems, or workflow automation platforms
- Experience with Bloomberg’s products or other financial data providers’ products
- Good understanding of the equity market, corporate actions or reference data
If this sounds like you:
Apply! If you think we're a good match. We'll get in touch to let you know the next steps!