• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets. • Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots). • Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation). • Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns. • Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning. • Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross‑domain interoperability and AI consumption. • Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows, ensuring alignment with governance standards and risk expectations. • Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms. • Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes. • Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.

• Develop & deploy azure databricks in a cloud environment using Azure Cloud services • ETL design, development, and deployment to Cloud Service • Interact with Onshore, understand their business goals, contribute to the delivery of the workstreams • Design and optimize model codes for faster execution

• Provide comprehensive capacity building and compliance assistance to AI/AN victim services programs • Plan and execute assistance activities including developing and advancing customized assistance plans • Assist programs in developing or enhancing victim services policies and procedures • Support recipients in resolving OJP monitoring issues and implementing corrective actions • Evaluate individual grantee needs and partner with grantees to implement customized assistance plans • Develop and foster truly collaborative partnerships with tribal communities • Facilitate trainings including webinars and peer learning exchanges • Assist with strategic planning • Identify and share culturally responsive, trauma informed practices

• Operate autonomously to provide linguistic QA and develop alignment resources. • Reviewing, annotating, and testing AI outputs for grammatical accuracy, naturalness, and strict cultural context. • Acting as a primary quality check during production to proactively identify and correct subtle cultural errors or awkward phrasing in the Māori. • Analyzing task quality trends and autonomously developing educational resources and feedback documentation to increase alignment between AI task outputs and campaign expectations. • Providing native-level language vetting during project scaling and offering specialized linguistic consultation throughout the production phase.