Oluwaseun L.

Key Skills

Software

Don't disclose

Google Cloud Vertex AI

Top Subject Matter

Geoscience (oil & gas) / machine learning training data curation

Materials/geoscience imaging (SEM) metadata extraction for ML data preparation

NLP/entity detection on electronic books

Top Data Types

Image

Text

Top Task Types

Data Collection

Text Generation

Entity (NER) Classification

Freelancer Overview

Data Scientist – Data Hub (dataset curation for AI training). Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Internal, and Proprietary Tooling. Education includes Master of Science, The University of Salford (2023) and Bachelor of Technology, Federal University of Technology (2018). AI-training focus includes data types such as Geospatial, Tiled Imagery, and Image and labeling workflows including Data Collection, Text Generation, and Entity (NER) Classification.

Labeling Experience

Data Scientist – Metadata extraction from SEM images using LLM + OCR

ImageText Generation

Developed an optimized workflow for extracting metadata from SEM images using an internally built LLM and OCR. Used PyTesseract in the pipeline to convert visual information into machine-readable text for subsequent processing. Achieved a reported 40% increase in efficiency of extraction and transformation activities supporting dataset preparation.• Extracted SEM image metadata via an internal LLM workflow.• Applied OCR using PyTesseract to structure extracted information.• Improved efficiency of extraction and transformation by 40% for downstream use.

2024 - 2025

Data Scientist – Data Hub (dataset curation for AI training)

Don't discloseData Collection

Built training datasets by curating diverse data types in collaboration with AI and R&D teams. Applied subject-matter expertise to classify and organize geoscience datasets from major clients for use in downstream ML workflows. Ensured accuracy and efficiency so the prepared data could support improved model accuracy and predictive performance.• Classified and organized client geoscience datasets (e.g., BP, Total, ExxonMobil).• Curated heterogeneous data types for training dataset readiness.• Focused on improving ML model accuracy and predictive performance through better dataset preparation.

2024 - 2025

Data Science Intern – Entity detection model and validation

Google Cloud Vertex AITextEntity (NER) Classification

Created and optimized a tailored entity detection model for electronic books to improve interactive reading experiences. Incorporated Wikipedia summary-based explanations to provide context alongside detected entities for the target audience. Ensured rigorous evaluation and validation of the supporting cloud functions that powered the entity-detection behavior.• Optimized an entity detection model for e-books.• Added Wikipedia summary-based entity explanations.• Conducted unit testing and validation for cloud functions (Google Cloud Vertex AI Workbench).• Queried and reconciled database discrepancies to maintain data consistency for the application.

2023 - 2023

Education

Work History