I am a data scientist with a Master of Science in Data Science and a strong track record in end-to-end ML lifecycle. I enjoy bridging frontier research with real-world impact by designing, training, and deploying predictive models, including Gradient Boosting, Neural Networks, and LLM solutions. I am proficient in Python, MLOps (Docker, MLflow), and cloud platforms (Azure, AWS), and I am passionate about Responsible AI, interpretability, and building scalable, secure systems in agile, cross-functional teams.
I have hands-on experience building robust data pipelines, automating model retraining, and collaborating with engineers and stakeholders to deliver measurable value. I am motivated to continue innovating in AI while ensuring safety, transparency, and accessibility.
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