Gad Abolo

Key Skills

Software

Appen

Clickworker

CrowdSource

CVAT

Data Annotation Tech

LabelImg

Label Studio

OneForma

Other

Top Subject Matter

No subject matter listed

Top Data Types

Document

Image

Text

Top Task Types

Bounding Box

Classification

Data Collection

Question Answering

Text Summarization

Freelancer Overview

I've been doing remote AI data labeling and annotation work for over five years now, mostly through platforms like Appen (joined mid-2020), OneForma (early 2021), Remotasks (late 2021), and Clickworker (since 2020). That's where I've racked up the bulk of my experience—labeling more than 50,000 data points in total, with a lot of it focused on retail and e-commerce stuff. Day to day, I do things like drawing precise bounding boxes on thousands of product images for object detection, classifying sentiment and spotting entities in customer reviews and surveys, rating AI responses on 1–10 scales (usually with a quick justification), and even frame-by-frame video tracking to analyze how shoppers move around stores. I always end up with really high accuracy ratings (98%+) because I'm careful about following guidelines to the letter. What makes my work a bit different is that I don't just label data—I actually get how it's used, thanks to my analytics background (I'm certified in Power BI, SQL, and Excel). On the side, I've freelanced directly with international retail clients similar to ASOS and HelloFresh, cleaning and structuring their sales and feedback data into stuff that feeds real dashboards and models (often showing 15–30% boosts in retention or efficiency). So I bring that bigger-picture understanding to labeling jobs, making sure the data I create is genuinely useful for training better models. I'm comfortable switching between tools like LabelImg, Label Studio, and CVAT

Labeling Experience

Customer Behavior Tracking in Retail Store Footage

Label StudioVideoBounding BoxClassification

Performed frame-by-frame video annotation on sample retail store footage, drawing bounding boxes around customers and staff, tracking movement paths across frames, and classifying actions such as browsing, product interaction, and queueing. Maintained temporal consistency in object IDs and action labels to support accurate behavior pattern analysis. This practice project developed my skills in video object tracking and action labeling, critical for training models in retail foot traffic and customer experience optimization.

Performed frame-by-frame video annotation on sample retail store footage, drawing bounding boxes around customers and staff, tracking movement paths across frames, and classifying actions such as browsing, product interaction, and queueing. Maintained temporal consistency in object IDs and action labels to support accurate behavior pattern analysis. This practice project developed my skills in video object tracking and action labeling, critical for training models in retail foot traffic and customer experience optimization.

2025

Object Detection & Bounding Box Annotation for Retail Product Images

LabelimgImageBounding BoxClassification

Practiced high-precision image annotation by labeling 200+ retail product images with accurate bounding boxes around items such as clothing, electronics, and household goods. Assigned classification tags for category, brand visibility, and display quality. Ensured consistent box placement and label accuracy following detailed guidelines, resulting in clean, structured annotations suitable for training object detection models in e-commerce applications. This hands-on project strengthened my ability to deliver fast, reliable image labeling with strong attention to visual detail.

Practiced high-precision image annotation by labeling 200+ retail product images with accurate bounding boxes around items such as clothing, electronics, and household goods. Assigned classification tags for category, brand visibility, and display quality. Ensured consistent box placement and label accuracy following detailed guidelines, resulting in clean, structured annotations suitable for training object detection models in e-commerce applications. This hands-on project strengthened my ability to deliver fast, reliable image labeling with strong attention to visual detail.

2025

Customer Survey Sentiment & Entity Classification

OtherTextEntity Ner ClassificationClassification

Annotated and classified hundreds of open-ended customer survey responses by labeling sentiment (positive, negative, neutral), extracting entities (product names, features, service aspects), and rating emotion intensity. Cleaned inconsistent text entries and applied consistent tags to highlight key preferences and pain points, transforming unstructured feedback into structured training-ready data. This work directly supported actionable business insights and mirrors text annotation requirements for NLP model training.

Annotated and classified hundreds of open-ended customer survey responses by labeling sentiment (positive, negative, neutral), extracting entities (product names, features, service aspects), and rating emotion intensity. Cleaned inconsistent text entries and applied consistent tags to highlight key preferences and pain points, transforming unstructured feedback into structured training-ready data. This work directly supported actionable business insights and mirrors text annotation requirements for NLP model training.

2025 - 2025

Retail Transaction Data Classification & Entity Annotation for Performance Analytics

OtherDocumentEntity Ner ClassificationClassification

Annotated and classified over 12 months of raw retail sales transaction data (thousands of records) by assigning accurate labels for region, product category, sales channel, performance tier, and key metrics. Performed entity extraction and tagging on fields such as customer segments, inventory items, and geographic locations to enable precise KPI tracking. Cleaned inconsistent entries, standardized categories, and evaluated underperforming areas through diagnostic rating, resulting in a structured, high-quality dataset that powered interactive dashboards and drove 15–20% modeled efficiency gains for the client. This work required strict adherence to business guidelines, consistency across large volumes, and attention to granular detail core strengths I bring to AI training data projects.

Annotated and classified over 12 months of raw retail sales transaction data (thousands of records) by assigning accurate labels for region, product category, sales channel, performance tier, and key metrics. Performed entity extraction and tagging on fields such as customer segments, inventory items, and geographic locations to enable precise KPI tracking. Cleaned inconsistent entries, standardized categories, and evaluated underperforming areas through diagnostic rating, resulting in a structured, high-quality dataset that powered interactive dashboards and drove 15–20% modeled efficiency gains for the client. This work required strict adherence to business guidelines, consistency across large volumes, and attention to granular detail core strengths I bring to AI training data projects.

2024 - 2024

Education

Work History