Alabi S.

Key Skills

Software

Other

Top Subject Matter

Customer sentiment analysis from text feedback

Sales analytics and KPI visualization

Data cleaning and reporting for analytics

Top Data Types

Document

Top Task Types

Classification

Data Collection

Freelancer Overview

Customer Sentiment Analysis project (Python-based sentiment classification). Core strengths include Other and Power BI. Education includes Bachelor’s Degree, Federal University Oye Ekiti (2026). AI-training focus includes data types such as Computer Code, Programming, and Document and labeling workflows including Classification and Data Collection.

Labeling Experience

Data Cleaning & Reporting project (Excel/Python datasets and visual reports)

OtherDocumentClassification

Performed data cleaning and reporting by preparing datasets in Excel and Python to produce clear visual reports. Standardized and cleaned inputs to improve reliability of downstream analysis. Organized outputs into readable reporting formats for interpretation. • Cleaned and preprocessed datasets in Excel/Python • Removed inconsistencies and improved data quality for reporting • Produced visual reports to communicate analysis results • Ensured cleaned data supported accurate interpretation

2024

AI Sales Dashboard project (Power BI dashboard for sales KPIs)

Data Collection

Built an AI sales KPI reporting pipeline by preparing sales data and visualizing key trends in an interactive Power BI dashboard. Focused on organizing relevant metrics to support analysis and interpretation. Communicated trends through dashboard elements to help stakeholders monitor sales performance. • Prepared sales dataset for KPI visualization • Configured Power BI dashboard components and visualizations • Highlighted KPIs and trends to support business decision-making • Ensured dashboard outputs were interpretable and actionable

2024

Customer Sentiment Analysis project (Python-based sentiment classification)

OtherClassification

Implemented a customer sentiment classification workflow using Python to process feedback text and derive actionable insights. Applied data preparation steps to make the dataset suitable for classification. Validated outputs by reviewing predicted sentiment results for usefulness to business stakeholders. • Ingested and cleaned customer feedback text for modeling • Performed sentiment classification using Python-based analysis • Translated classification results into actionable business insights • Presented findings in a clear, decision-oriented format

2024

Education

Work History