Lawal Abdulazeezfaruq

Key Skills

Software

CVAT

Doccano

Labelbox

Prodigy

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Text

Top Task Types

Data Collection

Object Detection

Segmentation

Text Generation

Text Summarization

Freelancer Overview

I am an AI and data professional with hands-on experience in AI training data, data labeling, and model evaluation across NLP, computer vision, and financial document analysis. I have worked on text classification tasks such as spam vs ham detection, intent classification, and content quality evaluation, as well as image-based annotation projects involving document understanding and biometric data. My experience includes preparing high-quality labeled datasets to support supervised learning, improving model accuracy, and validating AI outputs for consistency and relevance. In addition, I have practical exposure to labeling and structuring real-world fintech data, including bank transaction receipts, statements, and expense records extracted from PDFs and images. I am comfortable working with annotation tools, spreadsheets, and Python-based workflows, and I understand the importance of precision, edge-case handling, and clear labeling guidelines in AI training. With a strong analytical mindset and attention to detail, I consistently deliver reliable training data that enables machine learning models to perform effectively in production environments.

Labeling Experience

Financial Transaction Receipt Annotation for AI Model Training

Scale AIImageEntity Ner ClassificationClassification

This project focused on annotating and structuring financial transaction data from bank transfer receipts and payment confirmations in image and PDF formats. The primary goal was to prepare high-quality labeled datasets for training and evaluating AI models used in document understanding, expense tracking, and transaction reconciliation. My responsibilities included extracting and labeling key entities such as transaction date, sender and recipient details, account identifiers, transaction amount, currency, reference/narration, and transaction status. I performed document classification (successful vs failed transactions, transfer vs payment), validated OCR outputs, and flagged edge cases such as incomplete or ambiguous records. The project involved hundreds of transaction records, with strict adherence to labeling guidelines, consistency checks, and accuracy reviews to ensure reliable training data.

This project focused on annotating and structuring financial transaction data from bank transfer receipts and payment confirmations in image and PDF formats. The primary goal was to prepare high-quality labeled datasets for training and evaluating AI models used in document understanding, expense tracking, and transaction reconciliation. My responsibilities included extracting and labeling key entities such as transaction date, sender and recipient details, account identifiers, transaction amount, currency, reference/narration, and transaction status. I performed document classification (successful vs failed transactions, transfer vs payment), validated OCR outputs, and flagged edge cases such as incomplete or ambiguous records. The project involved hundreds of transaction records, with strict adherence to labeling guidelines, consistency checks, and accuracy reviews to ensure reliable training data.

2024 - 2025

Education

Work History