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Hendra Kurniawan

Hendra Kurniawan

Data Labelling

Indonesia flagJakarta, Indonesia
$15.00/hrIntermediateInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
TextText
VideoVideo

Top Task Types

Classification
Object Detection
Segmentation
Text Summarization
Translation Localization

Freelancer Overview

I have extensive experience in data labeling and AI training data preparation. I have worked with diverse datasets, including images, text, audio, and video, to ensure high-quality, accurately annotated inputs for machine learning models. My expertise covers a range of labeling techniques such as classification, segmentation, entity recognition, and transcription, tailored to various AI applications like product categorization, keyword processing, and image recognition. I’m skilled in executing annotation tasks. I achieved the best agent awards by maintaining strict quality control through detailed guidelines and review cycles, significantly enhancing model performance and reducing bias. What sets me apart is my strong analytical ability combined with meticulous attention to detail, ensuring consistency and precision in annotations even in complex or ambiguous cases. I’ve contributed to projects ranging from autonomous vehicle sensor data annotation to sentiment analysis training sets, demonstrating adaptability and domain knowledge across industries. Additionally, my understanding of AI workflows and collaboration with data scientists and engineers enables me to align labeling efforts with broader model goals, optimizing training data for better outcomes.

IntermediateEnglishIndonesianChinese Mandarin

Labeling Experience

Shopee SPU Image Annotation

Internal Proprietary ToolingImageClassificationObject Detection
In this project, I was responsible for annotating a large dataset of product images to enhance an AI-driven image recognition system aimed at optimizing e-commerce product categorization. The primary goal was to accurately label images according to predefined product categories, subcategories, and relevant attributes (such as color, style, and material), enabling the model to automatically classify products with high precision. Key tasks included developing detailed labeling guidelines to ensure consistency across thousands of images, using internal annotation tools to define category tags, and handle multi-label classification where products belonged to overlapping categories. I worked closely with data scientists to continuously refine the labels based on model feedback, improving dataset quality and supporting the iterative training process.

In this project, I was responsible for annotating a large dataset of product images to enhance an AI-driven image recognition system aimed at optimizing e-commerce product categorization. The primary goal was to accurately label images according to predefined product categories, subcategories, and relevant attributes (such as color, style, and material), enabling the model to automatically classify products with high precision. Key tasks included developing detailed labeling guidelines to ensure consistency across thousands of images, using internal annotation tools to define category tags, and handle multi-label classification where products belonged to overlapping categories. I worked closely with data scientists to continuously refine the labels based on model feedback, improving dataset quality and supporting the iterative training process.

2024 - 2025

Shopee SPU Text Annotation

Internal Proprietary ToolingTextSegmentationClassification
In this project, I managed the annotation of large-scale textual data extracted from product descriptions, titles, and specifications to support an AI-powered text recognition system aimed at optimizing product categorization in an e-commerce platform. The objective was to accurately label and categorize products based on key textual features such as brand names, product types, sizes, and other relevant attributes. I developed comprehensive annotation guidelines to ensure consistent labeling of product-related information, handling challenges like ambiguous terms, inconsistent formatting, and multiple attribute extraction. Using specialized text annotation tools, I tagged entities, normalized product attributes, and performed multi-label classification to capture nuanced category relationships.

In this project, I managed the annotation of large-scale textual data extracted from product descriptions, titles, and specifications to support an AI-powered text recognition system aimed at optimizing product categorization in an e-commerce platform. The objective was to accurately label and categorize products based on key textual features such as brand names, product types, sizes, and other relevant attributes. I developed comprehensive annotation guidelines to ensure consistent labeling of product-related information, handling challenges like ambiguous terms, inconsistent formatting, and multiple attribute extraction. Using specialized text annotation tools, I tagged entities, normalized product attributes, and performed multi-label classification to capture nuanced category relationships.

2023 - 2025

Education

U

Universitas Presiden

Bachelor, N/A

Bachelor
2015 - 2019

Work History

S

Shopee International Indonesia

Business Development Analyst

Jakarta
2023 - Present
T

Tokopedia

Sales and Business Operation

Jakarta
2021 - 2023