Senior Data Management Professional – Semantic Modelling - Economics, Hong Kong

Bloomberg is hiring a Senior Data Management Professional – Semantic Modelling - Economics, Hong Kong (Hong Kong SAR China). Level rates it ; you can apply on Level.

AI in this role

Senior data management professional to drive semantic modeling and data readiness strategies for AI-driven applications.

semantic-modelingtaxonomiesontologiesmetadata-standardsdata-governance

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 enhance our systems, products and processes - all while providing platinum customer support to our clients.

The Team:
The Economics Data team is responsible for onboarding, modelling, maintaining, and improving datasets that power Bloomberg's Economics products and client workflows. Our data supports the Bloomberg Terminal, BQL, Enterprise solutions, and other Bloomberg products. We lead a broad range of datasets, including macroeconomic, government, survey, forecast, time-series, and vendor-supplied data. Our mission is to deliver data that is accurate, timely, scalable, discoverable, interoperable, and ready for both client consumption and AI-driven applications!

The Role:
We are looking for a Senior Data Management Professional – Semantic Modelling to define and drive the semantic modelling strategy for Economics data. You will play a key role in advancing Bloomberg's Data for AI readiness strategy, with a focus on modelling and query readiness. Working closely with Data, Engineering, Product, and domain experts, you will develop semantic models, ontologies, taxonomies, and metadata standards that make Economics data discoverable, interoperable, reusable, and AI-ready.

We’ll trust you to:

Define and evolve semantic models, taxonomies, ontologies, and metadata standards
Design interconnected data models and knowledge structures that support client workflows, search, and AI applications
Establish standard processes for metadata, lineage, provenance, and data governance
Partner with Product, Engineering, and domain experts to deliver scalable, reusable data solutions
Audit existing data model and infrastructure; utilize industry standard data architecture & modeling with focus on interoperability
Drive data quality, interoperability, and FAIR data principles across the data lifecycle
Audit and improve existing models, processes, and standards, while mentoring colleagues and promoting semantic modelling standards
Research industry standards and best practices on data attribute and modeling requirements

You’ll need to have:

Bachelor's degree or equivalent experience in Economics, Statistics, Computer Science, Engineering, or a related field
Experience in semantic modelling, data management, governance, metadata, or data architecture and experience designing scalable, interoperable data models and data products
Good understanding of ontologies, taxonomies, metadata, lineage, and data lifecycle management
Technical proficiency in SQL, Python, or similar analytical tools
Project management skills and ability to prioritize and adapt to tasks accordingly
Strong stakeholder management, communication, and problem-solving skills.
Demonstrated continuous career growth within an organization
Fluency in both spoken and written English

We’d love to see:

Experience with Economics or time-series datasets.
Experience applying AI or machine learning to data management challenges.
Experience with knowledge graphs or semantic technologies.
Agile project delivery experience and/or CDMP certification.

If this sounds like you:Apply if you think we're a good match. We'll get in touch to let you know what the next steps are, but in the meantime feel free to have a look at this: https://www.bloomberg.com/professional
Learn more about our offices and benefits:Hong Kong | https://www.bloomberg.com/hongkong Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

How we rate this

Senior Data Management Professional – Semantic Modelling - Economics, Hong Kong at Bloomberg rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Senior Data Management Professional – Semantic Modelling - Economics, Hong Kong is an open job at Bloomberg.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Hong Kong, Hong Kong.
The job was posted on October 16, 2026.
Seniority: senior.
Applications are handled by Bloomberg. Apply on Bloomberg

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Semantic ModelingTaxonomiesOntologiesMetadata StandardsData Governance

Questions you could be asked

Tell me about a project where semantic modeling was part of your work. What did you do?
Tell me about a project where taxonomies was part of your work. What did you do?
Tell me about a project where ontologies was part of your work. What did you do?
Tell me about a project where metadata standards was part of your work. What did you do?
Tell me about a project where data governance was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Semantic Modeling, Taxonomies, Ontologies, Metadata Standards, and Data Governance. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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