AI Data Analyst Job at TRIMAH TECHNOLOGIES LLC, Columbus, OH

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  • TRIMAH TECHNOLOGIES LLC
  • Columbus, OH

Job Description

We are seeking an AI Data Analyst focused on Data Governance to support AI engineering initiatives by ensuring compliant, secure, and ethical use of data across AI systems. This role bridges governance and AI delivery, helping establish data quality, lineage, metadata, and regulatory alignment for modern AI platforms including RAG-based systems. The role is onsite, preferably in Columbus, OH, but open to Chantilly / Crystal City, VA.

Key Responsibilities

Define and enforce data governance policies for AI models and pipelines in partnership with engineering teams.

Implement data quality, lineage, and classification frameworks supporting training and inference workflows.

Ensure compliance with standards such as NIST AI RMF, ISO/IEC 42001, GDPR, CMMC, DFARS, and internal policies.

Develop and maintain metadata strategies including embeddings and vector store governance for RAG architectures.

Partner with security and compliance teams on risk assessments for AI data usage and model outputs.

Support responsible AI practices including bias detection, transparency, and explainability.

Guide data retention, lifecycle management, and secure handling of sensitive data (PII, CUI).

Required Skills & Qualifications

Bachelor's or Master's degree in Data Science, Information Governance, Computer Science, or related field.

Strong understanding of data governance principles, AI/ML workflows, and cloud environments (Azure preferred).

Experience with Microsoft Purview, Power Platform, or similar governance platforms.

Familiarity with AI model lifecycle, training data preparation, embeddings, and RAG strategies.

Knowledge of regulatory compliance (DFARS, CMMC, ITAR, FedRAMP) and ethical AI standards.

Excellent communication skills to translate technical requirements into clear governance policies.

Preferred / Nice to Have

Hands-on experience with Azure AI Foundry or Copilot Studio.

Experience with sensitivity labels, DLP, and data security controls.

Background working cross-functionally with engineering, compliance, and business stakeholders.

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