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AWS SageMaker
AppenCrowdSourceData Annotation TechTelusNo subject matter listed
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VideoI am a data scientist and ML engineer with hands-on experience in data labeling, annotation, and AI training data workflows. At Amazon, I have contributed to over 10 critical machine learning projects, working extensively with structured and unstructured data—images, text, audio, and video—to support model development in domains such as NLP, generative AI, and computer vision. My expertise includes performing high-accuracy tasks like bounding box annotation, segmentation, classification, and transcription, always ensuring data quality through rigorous validation and adherence to guidelines. I am skilled in Python, SQL, AWS SageMaker Ground Truth, Appen, and QuickSight, and have a proven track record of collaborating with data science teams to improve dataset accuracy and model performance. I thrive in fast-paced environments, consistently meeting tight deadlines while maintaining the highest standards for data integrity and operational efficiency.
Designed and implemented a scalable data labelling pipeline to create high-quality annotated datasets for training supervised machine learning models.
Master of Computer Applications, Computer Applications
Master of Computer Applications, Computer Application
Machine Learning Associate
System Engineer
