Bright Uzosike

Key Skills

Software

Appen

Axiom AI

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Computer Code Programming

Image

Video

Top Label Types

Action Recognition

Classification

Evaluation Rating

Object Detection

Prompt Response Writing SFT

Freelancer Overview

I am a data science and analytics professional with hands-on experience in data annotation and AI training data workflows, particularly within robotics and machine learning projects. My background includes evaluating and annotating operational datasets to improve model accuracy, analyzing failed outputs to guide retraining, and collaborating with AI development teams to enhance instruction-following AI systems. I am highly skilled in Python, SQL, Power BI, Tableau, and Scikit-learn, and have applied data cleaning, feature engineering, and rigorous model evaluation techniques across diverse domains such as consulting, HR analytics, and geospatial data. My approach emphasizes data quality, actionable insights, and clear communication of complex findings to technical and non-technical stakeholders alike. I am passionate about building robust datasets that power reliable AI solutions and am adept at using annotation tools and best practices to support high-quality model development.

Labeling Experience

Data Annotation Specialist

Scale AIVideoAction RecognitionEvaluation Rating

• Evaluated and annotated robotics operational data to improve AI/ML model accuracy, contributing to systematic performance benchmarking across instruction-following tasks • Analyzed failed model outputs, documenting discrepancies between expected and actual responses to inform iterative model retraining cycles • Collaborated with AI development teams to enhance robotics instruction comprehension, directly improving response generation quality

• Evaluated and annotated robotics operational data to improve AI/ML model accuracy, contributing to systematic performance benchmarking across instruction-following tasks • Analyzed failed model outputs, documenting discrepancies between expected and actual responses to inform iterative model retraining cycles • Collaborated with AI development teams to enhance robotics instruction comprehension, directly improving response generation quality

2025 - 2025

Education

Work History