Manager, GPS Knowledge Systems

Role Summary

Manager, GPS Knowledge Systems. A role within the Global Product Development and Supply (GPS) division, supporting downstream GPS use cases such as AI deployment and self-service analytics. Partners with stakeholders to design and implement semantic models and information architectures, leveraging semantic technologies to deliver business value.

Responsibilities

• Develop information models leveraging emerging technologies to deliver business value.
• Design semantic models and data ontologies to support GPS information model and optimal AI deployment.
• Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment).
• Evaluate high-ROI technologies for inclusion in the technology roadmap.
• Partner with stakeholders to capture business needs.
• Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders.
• Translate complex concepts for various stakeholders.

Qualifications

• Professional Experience
  • 1+ years of experience in Information Technology, data analytics, or related industries
  • 1+ year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases
  • Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments.
• Technical Expertise
  • Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling is desired.
  • Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying preferred.
  • Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data preferred.
  • Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS a plus.
  • Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval is a plus.
  • Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala).
  • Experience with cloud environments and services, preferably AWS.
  • Experience with DevOps principles for CI/CD pipelines.
  • Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc.
  • Experience deploying AI models is highly desirable.
  • Experience with systems using the Model Context Protocol (MCP) to interact with AI models is highly desirable.
  • Hands-on experience with agile methodologies and tools such as JIRA.
  • Experience with ELT and data engineering processes is a plus.
  • Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions is a plus.
  • Experience with API integration for data ingestion and extraction.
  • Proven experience guiding large, complex projects.
  • Solid communication skills to explain the business value of data model projects and operations.
  • A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement.
  • Ability to work effectively in a matrixed organization and across global locations.

Education

• A bachelor's degree in a quantitative or scientific discipline is required.
• Advanced degrees (MS or Ph.D.) in relevant fields are preferred.

Additional Requirements

• Occasional travel to BMS locations throughout the world is anticipated.