Shyank K.

Key Skills

Software

CVAT

Labelbox

Scale AI

SuperAnnotate

V7 Labs

Top Subject Matter

AI training dataset preparation (text labeling/classification)

Data Annotation & Labeling

Natural Language Processing (NLP) Basics

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Classification

Segmentation

Text Summarization

Prompt + Response Writing (SFT)

Transcription

Object Detection

Freelancer Overview

Aspiring AI Data Trainer and Data Labeling Specialist pursuing a B.Tech in Computer Science & Engineering from AKTU University (expected 2027). Possesses foundational knowledge of Artificial Intelligence, Machine Learning, data annotation, dataset preparation, and quality assurance processes. Skilled in Python, MS Excel, Google Sheets, Jupyter Notebook, and data validation techniques, with a strong focus on accuracy, attention to detail, and organized data management. Completed academic projects involving dataset classification, data cleaning, validation, and analytics-based reporting. Demonstrates strong analytical, problem-solving, and communication skills, with a keen interest in contributing to AI model development through high-quality labeled datasets. Seeking opportunities as an AI Data Trainer, Data Annotator, or Data Labeling Specialist to gain hands-on experience and support the development of reliable AI systems.

Labeling Experience

Fresher | Aspiring AI Data Trainer (annotation specialist focus)

TextEntity (NER) Classification

Demonstrated preparedness for AI data training through guideline-following and maintaining annotation accuracy for text-based datasets. Supports dataset preparation and validation steps to ensure labels align with defined categories and quality checks. Applies analytical skills to verify consistency and reduce annotation errors. • Followed annotation guidelines and accuracy expectations for text labeling tasks. • Assisted with data cleaning and validation to improve overall dataset quality. • Prepared and organized datasets for machine learning training workflows. • Performed basic text classification-oriented dataset structuring and verification.

2026 - Present

AI-Based Data Classification Project

TextClassification

Organized and classified datasets to support machine learning text classification training objectives. Conducted data cleaning and validation to improve dataset reliability before model usage. Ensured that prepared inputs met expected quality standards for downstream training workflows. • Organized and structured datasets for machine learning tasks. • Performed data cleaning and validation to improve dataset quality. • Supported text classification dataset preparation and labeling consistency. • Applied verification steps to reduce errors in training data.

2025

Education

Work History