Nahid Hasan

Results-driven AI Data Annotation Expert with professional experience at iMerit and extensive hands-on work across micro-tasking AI training platforms. Specializes in image and video labeling, bounding box annotation, polygon segmentation, and NER tagging for machine learning pipelines. Combines annotation expertise with a background in digital marketing and content moderation to deliver precise, pipeline-ready datasets. Certified in Prompt Engineering and Agentic AI.

Image & Video Data Annotator at iMerit (2026-02 – Present)

Perform precise image and video annotation for AI/ML model training datasets including bounding boxes, polygon segmentation, and classification tags. Maintain high accuracy standards aligned with project quality guidelines using CVAT and Roboflow tooling. Collaborate with team leads to ensure consistent labeling conventions across large-scale data batches.

• Perform precise image and video annotation for AI/ML model training datasets including bounding boxes, polygon segmentation, and classification tags.
• Maintain high accuracy standards aligned with project quality guidelines using CVAT and Roboflow tooling.
• Collaborate with team leads to ensure consistent labeling conventions across large-scale data batches.

Freelance Data Annotator — Image & Video at Various Micro-Tasking AI Training Platforms (Microworkers & similar) (2025-01 – Present)

Completed high-volume image labeling, video frame annotation, and content-relevance tasks across multiple AI training platforms. Applied bounding box, semantic segmentation, and object classification techniques to build supervised ML training datasets. Maintained top-performer accuracy scores and task completion rates consistently above platform benchmarks. Utilized OpenCV and CVAT to streamline annotation workflows and improve throughput.

• Completed high-volume image labeling, video frame annotation, and content-relevance tasks across multiple AI training platforms.
• Applied bounding box, semantic segmentation, and object classification techniques to build supervised ML training datasets.
• Maintained top-performer accuracy scores and task completion rates consistently above platform benchmarks.
• Utilized OpenCV and CVAT to streamline annotation workflows and improve throughput.

Digital Marketing & SEO Executive at Clipping Amazon (2023 – 2025)

Delivered SEO strategy, keyword research, and performance analytics driving measurable ranking improvements.

• Delivered SEO strategy, keyword research, and performance analytics driving measurable ranking improvements.

Sr. Content Moderator at Genex Infosys Ltd (2022 – 2023)

Moderated content and produced audience segmentation and performance reports across social media channels.

• Moderated content and produced audience segmentation and performance reports across social media channels.

BSc in Textile Engineering – European University of Bangladesh (2017)