Senior Staff Data Scientist, Ontology Modeling

GE Vernovas Gas Power Data Science organization is building an enterprise ontology and knowledge graph capability to give AI agents GenAI applications and advanced analytics a shared governed representation of the business. Were looking for a Senior Ontology & Knowledge Graph modeling to own the ontology and knowledge graph strategy across all of Gas Power including services engineering and commercial domains ensuring they interoperate as one coherent semantic layer rather than a set of individually correct but disconnected models. Youll build the semantic connective tissue that lets Gas Power derive intelligence from its industrial data leading the shift from traditional data management to an AI-ready semantic ecosystem that enables advanced diagnostics predictive maintenance and strategic decision-making.
This is a program level role. You remain technically hands on enough to build and debug models when it matters but your time is weighted toward setting modeling standards resolving cross-domain conflicts and acting as the final technical authority on ontology. You own how the organization scales its model-building capability training approach and delivery process for contractors FDEs (Forward Deployed Engineers) and SMEs across the entire program and you are accountable for the organizations overall ontology capability not just the output of any single domain.
You will define and own the semantic model governance framework end to end versioning policy lifecycle access model and how governance holds up as adoption scales and you will own the platform selection decision and long-term roadmap.

Roles and Responsibilities

• Own the ontology and knowledge graph strategy across all Gas Power domains: services engineering and commercial ensuring domain models interoperate as one coherent semantic layer.

• Set enterprise-wide modeling standards and patterns (OWL 2 RDF/RDFS SHACL SPARQL) that all domain models must follow.

• Resolve cross-domain modeling conflicts and serve as the final technical authority when domain models compete or overlap.

• Design and own the organizations model for scaling ontology work: how contractors FDEs and SMEs are staffed trained and deployed across the full program.

• Build and evolve the training curriculum that brings SMEs to self-sufficiency in building and maintaining their own domain models.

• Own the organizations overall ontology building capability measured not by any single domains output but by how well the program scales without bottlenecking on any one person.

• Define the model approval framework: review criteria review board/process and escalation path for contested or high-risk models.

• Serve as final arbiter on contested or high-risk model approvals while delegating day-to-day approvals within the defined framework.

• Own the semantic model governance framework end to end: versioning policy model lifecycle access model and metadata/lineage management.

• Ensure governance scales as the knowledge graph grows auditing for drift inconsistency and standards erosion across domains.

• Partner with the GenAI/ML and AI platform teams to ensure the knowledge graph is the grounding layer for RAG and agentic workflows program-wide.

• Communicate modeling trade-offs and delivery progress clearly to technical teams and senior stakeholders.

• Contribute reusable standards reference documentation and mentoring that strengthen ontology and semantic modeling capability across the team.

• Bachelors degree in computer science information science data science engineering or a related field or equivalent practical experience.

• 4-6 years of professional experience in data modeling semantic technologies or knowledge engineering including at least 1-2 years working directly with ontologies.

• Professional experience delivering data models semantic technologies or knowledge engineering solutions including direct work with ontologies or knowledge graphs.

• Hands-on proficiency with OWL 2 RDF/RDFS SHACL and SPARQL.

• Experience with at least one ontology graph or semantic modeling platform or tool such as Neo4j Protégé Palantir Foundry or Atlan.

• Working knowledge of modern cloud data environments and the integration patterns required to connect semantic layers to enterprise data products.

• Demonstrated ability to independently deliver a defined technical scope within a broader architecture and product roadmap.

• Strong communication and stakeholder-management skills with the ability to convert ambiguous requirements into clear semantic models and recommendations.

• Demonstrated ability to work independently on a defined scope while collaborating within a broader technical roadmap.

Preferred Qualifications

• Experience in an industrial energy or manufacturing environment (services demand asset performance or engineering data domains a plus).

• Exposure to GenAI/LLM applications particularly RAG architectures grounded in structured knowledge.

• Familiarity with MCP (Model Context Protocol) or similar agent-to-data integration patterns.

• Experience contributing to platform evaluation or architecture decision documents for executive audiences.

• Knowledge of data governance metadata management or MLOps practices (MLflow or similar).

For candidates applying to a U.S. based position the pay range for this position is between $119200.00 and $198600.00. The Company pays a geographic differential of 110% 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors including the candidates experience education and skill set.

Bonus eligibility: discretionary annual bonus.

This posting is expected to remain open for at least seven days after it was posted on October 08 2026.

Available benefits include medical dental vision and prescription drug coverage; access to Health Coach from GE Vernova a 24/7 nurse-based resource; and access to the Employee Assistance Program providing 24/7 confidential assessment counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance adoption assistance paid parental leave disability benefits life insurance 12 paid holidays and permissive time off.

GE Vernova Inc. or its affiliates (collectively or individually GE Vernova) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate amend suspend replace or modify its benefit plans and programs at any time and for any reason in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.