Duke Mfalme

Key Skills

Software

Mindrift

Top Subject Matter

General AI training data for text models

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Top Data Types

Text

Image

Document

Top Task Types

Classification

Freelancer Overview

I have hands-on experience in AI training data and data annotation through my work with Mindrift (2023–2024), where I contributed to preparing high-quality datasets used in machine learning model development. My responsibilities included text annotation, classification, data validation, and quality review while strictly following annotation guidelines to ensure accuracy and consistency. I worked on labeling tasks involving content categorization, sentiment analysis, and structured data preparation, helping improve model performance through precise and reliable annotations. In addition to annotation work, I bring a strong analytical background from data analytics and economics, with skills in data cleaning, preprocessing, and quality assurance using tools such as Excel, SQL, Python, and statistical methods. I am highly detail-oriented, capable of maintaining accuracy in large-scale repetitive tasks, and experienced in remote collaboration within distributed AI teams. My combination of analytical thinking, data quality awareness, and commitment to ethical AI development enables me to consistently deliver dependable training data for AI systems.

Labeling Experience

Data Annotator

MindriftTextClassification

As a Data Annotator at Mindrift, I performed large-scale data labeling and annotation tasks supporting machine learning and AI model development. I annotated text datasets for classification, categorization, sentiment analysis, and entity recognition tasks. I reviewed and validated annotated datasets to ensure compliance with project guidelines and accuracy benchmarks. • Applied annotation standards consistently to improve model training reliability. • Identified ambiguous data cases and escalated them for guideline refinement. • Maintained high annotation accuracy while meeting strict productivity targets. • Conducted quality checks and peer reviews to minimize labeling inconsistencies.

As a Data Annotator at Mindrift, I performed large-scale data labeling and annotation tasks supporting machine learning and AI model development. I annotated text datasets for classification, categorization, sentiment analysis, and entity recognition tasks. I reviewed and validated annotated datasets to ensure compliance with project guidelines and accuracy benchmarks. • Applied annotation standards consistently to improve model training reliability. • Identified ambiguous data cases and escalated them for guideline refinement. • Maintained high annotation accuracy while meeting strict productivity targets. • Conducted quality checks and peer reviews to minimize labeling inconsistencies.

2023 - 2024

Education

Work History