Adeniyi Lawal

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Label Studio

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Freelancer Overview

Master’s-level Business Analytics specialist with experience evaluating machine learning model behaviour, analysing fairness–accuracy trade-offs, and producing structured rubric-based assessments of analytical and written outputs. Strong background in logical consistency review, academic research synthesis, and English-language content evaluation. Skilled in identifying bias risks, classifying complex information, and delivering high-accuracy, evidence-based feedback for AI training and LLM evaluation workflows.

Labeling Experience

Machine Learning Fairness & Output Evaluation – MSc Research Project

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Evaluated and compared multiple machine learning classifiers (logistic regression, random forest, and gradient boosting) to assess fairness–accuracy behaviour across demographic groups. Applied structured rubrics to analyse model outputs, identify proxy bias risks, and produce logically consistent, evidence-based written feedback. Performed content classification, research synthesis, and high-precision English-language analytical review aligned with ethical AI governance.

Evaluated and compared multiple machine learning classifiers (logistic regression, random forest, and gradient boosting) to assess fairness–accuracy behaviour across demographic groups. Applied structured rubrics to analyse model outputs, identify proxy bias risks, and produce logically consistent, evidence-based written feedback. Performed content classification, research synthesis, and high-precision English-language analytical review aligned with ethical AI governance.

2024 - 2025

Education

Work History