Goodness Ojeaga

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Appen

Other

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Computer Code Programming

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Text

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Computer Programming Coding

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Fine Tuning

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Freelancer Overview

I am a detail-oriented professional with hands-on experience in data preprocessing, cleaning, and annotation, supporting AI and machine learning projects across diverse domains. My technical expertise includes Python, SQL, Scikit-learn, TensorFlow, PyTorch, and tools like Power BI, Excel, and Azure, enabling me to collect, clean, and format large datasets for high-quality training data. I have developed and optimized machine learning models for predictive analytics, and I am skilled in data visualization and statistical analysis to ensure data integrity. My background also includes troubleshooting data pipelines, collaborating with cross-functional teams, and maintaining rigorous documentation, all of which contribute to delivering reliable and accurate datasets for AI and data-driven solutions.

Labeling Experience

Data/AI Contributor, Appen Ltd

AppenTextEntity Ner Classification

As a Data/AI Contributor at Appen Ltd, I executed complex annotation tasks over multiple datasets such as Named Entity Recognition (NER), sentiment analysis, and semantic segmentation. I ensured data quality by performing rigorous auditing to detect bias, hallucinations, or safety violations. My work included authoring and refining prompts for generative AI models and providing localization feedback to enhance NLP model performance. • Conducted NER, sentiment, and semantic segmentation annotations on multilingual textual datasets. • Performed qualitative audits of annotated data to ensure 95%+ guideline adherence. • Developed test prompts to evaluate both creative and logical model boundaries. • Delivered linguistic and localization feedback to improve Natural Language Processing models.

As a Data/AI Contributor at Appen Ltd, I executed complex annotation tasks over multiple datasets such as Named Entity Recognition (NER), sentiment analysis, and semantic segmentation. I ensured data quality by performing rigorous auditing to detect bias, hallucinations, or safety violations. My work included authoring and refining prompts for generative AI models and providing localization feedback to enhance NLP model performance. • Conducted NER, sentiment, and semantic segmentation annotations on multilingual textual datasets. • Performed qualitative audits of annotated data to ensure 95%+ guideline adherence. • Developed test prompts to evaluate both creative and logical model boundaries. • Delivered linguistic and localization feedback to improve Natural Language Processing models.

2022 - 2025

Data Scientist (Intern) , British Airways Data Science

OtherComputer Code ProgrammingClassificationEvaluation Rating

• Completed a simulation focusing on how data science is a critical component of British Airways success • Scraped and analyzed customer review data to uncover findings • Built a predictive model to understand factors that influence buying behaviour

• Completed a simulation focusing on how data science is a critical component of British Airways success • Scraped and analyzed customer review data to uncover findings • Built a predictive model to understand factors that influence buying behaviour

2024 - 2024

Data Scientists (Intern), Boston Consulting Group

OtherComputer Code ProgrammingClassificationFine Tuning

• Completed a customer churn analysis simulation for XYZ Analytics, demonstrating advanced data analytics skills, identifying essential client data and outlining a strategic investigation approach. • Conducted efficient data analysis using Python, including Pandas and NumPy. • Employed data visualization techniques for insightful trend interpretation. • Completed the engineering and optimization of a random forest model, achieving an 85% accuracy rate in predicting customer churn. • Completed a concise executive summary for the Associate Director, delivering actionable insights for informed decision making based on the analysis.

• Completed a customer churn analysis simulation for XYZ Analytics, demonstrating advanced data analytics skills, identifying essential client data and outlining a strategic investigation approach. • Conducted efficient data analysis using Python, including Pandas and NumPy. • Employed data visualization techniques for insightful trend interpretation. • Completed the engineering and optimization of a random forest model, achieving an 85% accuracy rate in predicting customer churn. • Completed a concise executive summary for the Associate Director, delivering actionable insights for informed decision making based on the analysis.

2023 - 2023

Education

Work History