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Freelancer Overview

I am passionate about working with data and have hands-on experience in data validation, anomaly detection, and building robust data pipelines using Python and SQL. My background includes developing and maintaining scripts for data quality checks and ETL processes in enterprise environments, where I ensured accurate, reliable data for decision-making and reporting. I have applied advanced data analysis techniques and built machine learning models for real-world applications, such as credit card fraud detection and influence maximization in social networks, utilizing tools like Scikit-learn, NumPy, and Pandas. My experience spans automating data workflows, validating large datasets, and collaborating on cross-functional teams to deliver high-quality, annotated data for AI and analytics projects. I am detail-oriented, committed to data integrity, and eager to contribute to impactful AI training data initiatives.

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