Manoj

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Task Types

Classification

Object Detection

Evaluation Rating

Freelancer Overview

I am a data analyst with hands-on experience in data labeling, data validation, and data cleaning for both structured and unstructured datasets. My expertise includes using Python, SQL, and Excel to prepare, annotate, and verify data, ensuring high accuracy and consistency for AI and machine learning workflows. I have worked on NLP projects such as sentiment analysis and topic modeling, including research on meme sentiment classification and topic extraction from research articles. I am skilled at translating complex analytical findings into clear documentation and collaborating with teams to improve data reliability and process efficiency. My background in computer science and strong analytical skills enable me to quickly learn new tools and deliver quality AI training data for diverse domains.

Labeling Experience

Data Labelling

LabelboxImageClassificationObject Detection

Worked on an Image Data Labeling project using Labelbox, focused on image classification and evaluation/rating tasks to support LLM and AI model development. The project involved classifying images into predefined categories and evaluating image outputs based on quality, relevance, and accuracy guidelines. Performed data labeling, validation, and quality evaluation to ensure consistency and high annotation standards. Actively reviewed and rated labeled data to improve dataset reliability for model training and evaluation. Collaborated within a quality-controlled workflow to maintain accuracy, reduce errors, and support effective AI/ML model performance.

Worked on an Image Data Labeling project using Labelbox, focused on image classification and evaluation/rating tasks to support LLM and AI model development. The project involved classifying images into predefined categories and evaluating image outputs based on quality, relevance, and accuracy guidelines. Performed data labeling, validation, and quality evaluation to ensure consistency and high annotation standards. Actively reviewed and rated labeled data to improve dataset reliability for model training and evaluation. Collaborated within a quality-controlled workflow to maintain accuracy, reduce errors, and support effective AI/ML model performance.

2023 - 2023

Education

Work History