Used Tools & Technologies
LLM GenAIRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 3
Machine Learning @ 3
Leadership @ 3
Communication @ 3
Jira @ 2
Technical Leadership @ 3
Audit @ 3
Generative AI @ 3
AI @ 3
Data Modeling @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg runs on data. Our products are fueled by powerful information. The Data organization is responsible for delivering data, news, and analytics through innovative technology quickly and accurately. The Data Management and Operations (DMO) department supports development, enablement and implementation of data management best practices to deliver "ready-to-use" data.
As a Project Manager in the Knowledge Graph Group you will be a technical leader across the organization, solving problems and devising solutions for data challenges. You will orchestrate work across teams—from inception and modeling, through integration into the Semantic Platform and BQL, and into engineering implementation in user-facing terminal applications. A key focus is modernizing workflows by championing AI inclusion, increasing automation, system efficiency, and improving process and collaboration speed.
Responsibilities
- Enable technical discussions to ensure alignment with system design, scalability, and best practices.
- Champion AI & automation: identify and advocate for inclusion of AI and Machine Learning across the data lifecycle to automate manual processes and increase efficiency.
- Audit existing data models and infrastructure to promote interoperability and prevent redundant pipelines.
- Orchestrate technical delivery: coordinate ontologists, platform integration engineers, data practitioners, and software engineers to meet commitments.
- Design interconnected data models and knowledge organization structures (taxonomies/ontologies) that conceptualize knowledge across domains.
- Manage complex, cross-functional programs: plan, execute, and deliver programs, ensuring milestones and deliverables are met on time and in-scope.
- Bridge product and technical leadership: act as the primary link between product owners, technical leads, and individual contributors, removing obstacles to collaboration.
Requirements
- Proven experience managing multiple stakeholders, deadlines, and competing priorities across a complex organization.
- Technical appreciation of data management, including data modeling, metadata management, and the software development life cycle (SDLC).
- Demonstrated ability to translate business requirements into program objectives and deliver system design and implementation across teams.
- Excellent communication skills, able to explain complex technical topics (including AI/ML concepts) to audiences from leadership to individual contributors.
Preferred / Nice to Have
- Experience identifying use cases for Large Language Models (LLMs) or Generative AI to enhance data discovery, classification, or metadata generation.
- Familiarity with collaborative platforms such as MIRO and JIRA, and enthusiasm for championing new collaborative tools (including AI-assisted tools).
- Exposure to semantic technologies, metadata systems, linked data, and/or knowledge graphs.
- Understanding of Data Governance and Data Management, supported by industry certifications such as DAMA CDMP or DCAM.
- Knowledge of FAIR principles for data (findable, accessible, interoperable, reusable).
Benefits
- Salary range: 110000 - 140000 USD annually + Benefits + Bonus.
- Comprehensive benefits that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability, 401(k) with match, life insurance, and various wellness programs. (The Company does not provide benefits directly to contingent workers/contractors and interns.)
Location & Application
- Location: New York
- Apply via the Bloomberg careers site (links provided in the original posting).