AI Data Analyst

Role Overview

• 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.
• Assist 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 teams 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).
• 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.

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.

Tech Stack

• SQL

Benefits

• Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
• Life Assurance Policies: Providing financial security for your loved ones.
• Modern Family Benefits: Support for maternity, paternity, and adoption needs.
• Long Service Award: Recognition for your dedication and loyalty.
• Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
• Flexible Benefits Plan : Offering you wider choice of services and products Employee Assistance Program : Access support for personal and work-related challenges.
• Flexible Working Arrangements: Balance work and personal life effectively.
• Access to Learning and Development Resources: Empowering your professional growth.