AI Data Analyst

About the role

We are seeking an AI Data Analyst to support teams in preparing and maintaining AI-ready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality, metadata, and governance.

Responsibilities

• Work with product and delivery teams to assess whether datasets and content are fit for AI use cases.
• Help teams understand and apply AI data readiness standards, including quality, freshness, metadata, and access expectations.
• Identify common data issues that impact AI outcomes (e.g., stale data, unclear ownership, missing metadata) and recommend remediation steps.
• Contribute to repeatable checklists, guidance, or documentation that help teams prepare data for AI.
• Support data quality checks focused on accuracy, completeness, consistency, and timeliness for AI-consumed data.
• Aid in monitoring and validating data freshness and relevance, escalating issues to engineering or data owners as needed.
• Help teams improve data clarity and usability to reduce ambiguity in AI outputs.
• Assist in improving metadata, documentation, and business descriptions so AI systems can better interpret content.
• Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning (in coordination with engineering teams).
• Promote good content hygiene practices (clear structure, consistent naming, well-scoped documents).
• Support the upkeep and documentation of approved data sources used by AI solutions.
• Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.
• Collaborate with AI and platform teams on data inclusion/exclusion decisions without owning technical implementation.
• Help teams align AI-consumed data with enterprise governance requirements, including classification, access controls, and retention.
• Support basic data lineage and ownership documentation for AI-relevant datasets.
• Partner with governance and security teams by surfacing risks or gaps; does not act as final approval authority.

Requirements

• Proven experience in data analysis, analytics engineering, data operations, or data quality roles.
• Good understanding of data quality principles and how poor data impacts downstream systems.
• Experience working with structured and unstructured data (tables, files, documents, knowledge assets).
• Proficiency in SQL and comfort investigating data issues.
• Familiarity with data governance fundamentals (classification, access controls, ownership, retention).
• Strong communication skills and ability to explain data concepts to non-technical stakeholders.

Preferred Qualifications

• Exposure to AI-enabled products, copilots, or search-based solutions.
• Basic familiarity with AI data concepts such as semantic search, embeddings, or retrieval patterns.
• Experience working in enterprise or regulated environments.
• Experience contributing to standards, playbooks, or shared data practices.