Freelancer

Key Skills

Software

Other

Top Subject Matter

AI/system monitoring and behavioral failure taxonomy labeling from interaction logs

Top Data Types

Text

Top Task Types

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Freelancer Overview

Data Analyst & AI Evaluation Specialist — AI interaction record analysis and evaluation. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Science, VIT University (2027) and Bachelor of Technology, Jamia Millia Islamia. AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Data Analyst and AI Evaluation Specialist - Filo

TextClassification

In this role, you analyzed structured AI interaction records to identify behavioral patterns, failure modes, and non-stationary performance trends. You designed classification frameworks and failure taxonomies to support consistent evaluation across hallucination, reasoning breakdown, instruction drift, and multi-step task failures. You built Python-based workflows for data quality assessment, model monitoring, and reproducible reporting using common data and ML tooling. • Analyzed 3,000+ structured AI interaction records for performance trends and behavioral drift • Built classification frameworks and failure taxonomies for common model failure modes • Developed Python workflows for structured analysis, data quality assessment, and monitoring • Produced reproducible reporting to support AI evaluation and insights

2022 - Present

Data Analyst & AI Evaluation Specialist — AI interaction record analysis and evaluation

Other

Contributed to AI interaction record analysis to identify behavioral patterns and model failure modes using structured classification frameworks. Conducted evaluation-oriented monitoring of non-stationary performance trends across multiple AI interaction types. Supported reproducible reporting pipelines for model behavior and failure taxonomy tracking. • Analyzed 3,000+ structured AI interaction records. • Built classification frameworks and failure taxonomies (hallucination, reasoning breakdown, instruction drift, multi-step task failure). • Developed Python workflows for data quality assessment and model performance monitoring. • Focused on evaluating longitudinal, non-stationary behavior signals for monitoring.

2022 - Present

Education

Work History