Key Skills

Freelancer Overview

With over 7 years of experience in high-stakes data governance and enterprise-wide reporting, I specialize in the architectural integrity of datasets required for high-performance AI models. My expertise lies in data validation, cleaning, and reconciliation, ensuring that ground-truth data is accurate, consistent, and audit-ready. Having led data initiatives for the Minnesota Department of Commerce, I possess a deep understanding of maintaining structured performance indicators and managing the full data lifecycle—from complex SQL-driven extraction to the development of rigorous quality assurance frameworks that mirror the requirements of supervised learning and RLHF (Reinforcement Learning from Human Feedback) pipelines. What sets me apart is my ability to manage the human-in-the-loop process with a lead-level perspective. I am adept at creating risk assessment frameworks and data collection protocols that ensure training data is not only labeled but also contextually relevant and free of bias. My experience serving as a primary liaison between business units and IT teams (MNIT) allows me to scale data labeling operations while maintaining the strict compliance and data security standards necessary for sensitive government, financial, and regulatory AI applications.

Labeling Experience

Education

Work History