Feyisayo A.

Key Skills

Software

Other

Labelbox

Micro1

Mercor

OneForma

SuperAnnotate

Toloka

Top Subject Matter

Transactional/product-segment analytics and data quality tagging

AI Response Evaluation & Fact-Checking (Simulation)

E-commerce — Product Categorization & Data Enrichment

Top Data Types

Document

Image

Text

Top Task Types

Classification

Object Detection

Text Generation

Question Answering

Transcription

Text Summarization

Data Collection

Freelancer Overview

Data Analyst (Project-Based) — Independent/Consulting (Remote). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Obafemi Awolowo University (2028). AI-training focus includes data types such as Document and labeling workflows including Classification.

Labeling Experience

Data Analyst (Project-Based) — Independent/Consulting (Remote)

OtherDocumentClassification

Performed structured data tagging and classification on transactional and product-segment records to create annotation-ready datasets. Applied quality checks by validating consistency, flagging data quality issues, and documenting labeling decisions for traceability. Built labeling logic and segment taxonomy from scratch to support downstream dashboard reporting and analytics. • Tagged and classified product-segment data for loss-making lines • Established segment taxonomy and labeling logic • Ensured consistent formatting and traceable annotation documentation • Validated thousands of records and resolved edge-case inconsistencies

2024 - Present

Data Analytics Simulation Contributor — Deloitte Australia Job Simulation (Forage)

OtherDocumentClassification

Processed and labeled operational inefficiency data within a simulated client dataset using dynamic filtering logic to surface meaningful patterns. Structured the labeled/annotated findings into a client-ready narrative to demonstrate translation of annotated data into actionable insights. Maintained consistency across the end-to-end analytics workflow from raw data intake to final annotated output. • Applied dynamic filtering logic to highlight patterns • Labeled operational inefficiency data in the simulation • Converted labeled outputs into a narrative report • Ensured consistency across the full analytics workflow

2024 - 2024

Education

Work History