Rasheed Adeoti

Key Skills

Software

AWS SageMaker

Appen

Data Annotation Tech

Labelbox

CVAT

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Image

Text

Video

Top Label Types

Computer Programming Coding

Data Collection

Evaluation Rating

Prompt Response Writing SFT

Freelancer Overview

I am an applied mathematician and data scientist with hands-on experience supporting AI training, data annotation, and model evaluation across multidisciplinary projects. My background includes building and evaluating machine learning models, annotating and analyzing complex datasets, and validating solutions through mathematical rigor and programming expertise in Python, SQL, and MATLAB. I have contributed to research in optimization, predictive modeling, and public health data analysis, including projects like forecasting COVID-19 dynamics and predicting obesity levels using real-world data. My strong communication and teaching skills enable me to clearly explain abstract concepts and ensure high-quality, reliable training data for AI systems. I am passionate about leveraging my analytical and technical abilities to deliver precise, impactful results in data labeling and AI-driven projects.

Labeling Experience

Mathematical Problem Image Annotation for OCR and AI Learning system

CVATImageBounding BoxClassification

Labelled and annotated images of handwritten and printed mathematical problems for AI training. Tasks included bounding boxes for equations, symbols, and diagrams; classification of problem types, and OCR transcription of mathematical expressions to support automated grading and intelligent tutoring systems. Ensured high annotation accuracy and consistency for machine learning and computer vision applications in educational technology.

Labelled and annotated images of handwritten and printed mathematical problems for AI training. Tasks included bounding boxes for equations, symbols, and diagrams; classification of problem types, and OCR transcription of mathematical expressions to support automated grading and intelligent tutoring systems. Ensured high annotation accuracy and consistency for machine learning and computer vision applications in educational technology.

2025 - 2025

Education

Work History