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Anastasia Fedortsova

Russia flagMoscow, Russia
Expert

Key Skills

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Top Data Types

ImageImage

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Freelancer Overview

I have over three years of experience working with AI training data and data labeling across a variety of domains, including natural language processing, computer vision, and content moderation. My work has involved annotating large datasets with high accuracy, developing and refining labeling guidelines, and performing quality assurance to ensure consistency and reliability. I am experienced with tools such as labeling platforms, spreadsheet-based workflows, and task management systems, and I understand the importance of clear taxonomy design and edge-case handling in building high-quality datasets. What sets me apart is my strong attention to detail combined with an analytical mindset. I’ve contributed to projects that required nuanced judgment, such as sentiment analysis, entity recognition, and image classification under ambiguous conditions. I am also comfortable collaborating with cross-functional teams, providing feedback to improve annotation processes, and adapting quickly to new project requirements. My ability to balance speed with precision ensures that I consistently meet performance targets without compromising data quality.

Expert

Labeling Experience

AI Training Data Specialist – NLP & Multi-domain Annotation

TextClassification
Worked on large-scale AI training data projects involving both text and image annotation. For text data, performed tasks such as sentiment analysis, intent classification, named entity recognition (NER), and content moderation across diverse datasets including customer reviews, chat logs, and social media content. For image data, conducted classification and tagging tasks to support computer vision models. Handled datasets ranging from thousands to millions of data points, ensuring high accuracy and consistency. Followed detailed annotation guidelines and contributed to their improvement by identifying ambiguities and edge cases. Regularly performed quality assurance checks, peer reviews, and validation tasks to maintain data integrity and meet strict client benchmarks (typically 95%+ accuracy requirements).

Worked on large-scale AI training data projects involving both text and image annotation. For text data, performed tasks such as sentiment analysis, intent classification, named entity recognition (NER), and content moderation across diverse datasets including customer reviews, chat logs, and social media content. For image data, conducted classification and tagging tasks to support computer vision models. Handled datasets ranging from thousands to millions of data points, ensuring high accuracy and consistency. Followed detailed annotation guidelines and contributed to their improvement by identifying ambiguities and edge cases. Regularly performed quality assurance checks, peer reviews, and validation tasks to maintain data integrity and meet strict client benchmarks (typically 95%+ accuracy requirements).

2022 - 2025

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