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Mindrift

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Freelancer Overview

I have over two years of experience in cheminformatics and AI-driven drug discovery, where my primary focus has been on developing and validating machine learning models, curating and harmonizing complex biological datasets, and building high-quality data pipelines for computational workflows. My expertise spans data labeling and annotation for QSAR modeling, virtual screening, pharmacophore modeling, and molecular dynamics simulations, ensuring robust and accurate training data for AI/ML applications in small-molecule drug discovery and related domains. I am proficient in Python and R, comfortable working in Linux and Google Colab environments, and have collaborated closely with cross-functional teams to translate scientific requirements into actionable data solutions. My background includes leading data curation efforts, facilitating training workshops, and contributing to both internal and client-facing R&D programs, making me well-versed in the end-to-end process of generating and managing high-quality training data for AI systems.

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