Babayemi S.

Key Skills

Software

No software listed

Top Subject Matter

Meteorology and aviation weather forecasting

Customer churn analytics

Customer churn prediction

Top Data Types

Document

Image

Text

Top Task Types

Data Collection

Classification

Text Generation

Freelancer Overview

Intern – Meteorological Data Analysis | Nigerian Meteorological Agency. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N, A, and Python (pandas. Education includes Bachelor of Technology, Federal University of Technology Akure (2019). AI-training focus includes data types such as Document, Computer Code, and Programming and labeling workflows including Data Collection, Evaluation, and Rating.

Labeling Experience

Lloyds Banking Group Data Science Job Simulation – Forage

Classification

Developed a customer churn prediction model using Random Forest and ensemble machine learning methods in a job simulation context. Applied preprocessing steps including missing value imputation, categorical encoding, and feature scaling. Evaluated model quality using ROC-AUC and analyzed feature importance to extract business insights. • Built churn prediction models with Random Forest and ensembles • Implemented preprocessing pipelines (imputation, encoding, scaling) • Computed ROC-AUC and used metrics to guide evaluation • Visualized feature importance and produced insight-focused outputs

2026 - 2026

BCG Data Science Job Simulation – Forage

Executed an end-to-end customer churn analysis in a job simulation setting, including data investigation and predictive modeling. Built and optimized a Random Forest classifier using feature engineering with pandas and NumPy, targeting strong recall performance. Delivered an executive summary of actionable churn drivers derived from modeled results. • Modeled customer churn using Random Forest with feature engineering • Tuned and optimized the classifier to achieve a 75% recall rate • Performed exploratory analysis to identify key churn drivers • Communicated findings to business stakeholders via an executive summary

2026 - 2026

British Airways Data Science Job Simulation – Forage

Text Generation

Scraped and analyzed customer review data to identify sentiment patterns and service pain points in a job simulation. Built predictive modeling workflows to identify factors influencing customer buying behavior. Demonstrated a complete data science pipeline from data collection through modeling and actionable insights. • Collected text data via scraping for sentiment and pain-point analysis • Modeled customer buying behavior using engineered features • Extracted sentiment/service insights from review text • Ran end-to-end workflow from collection to final interpretation

2025 - 2025

Intern – Meteorological Data Analysis | Nigerian Meteorological Agency

DocumentData Collection

Analyzed meteorological datasets, satellite imagery, and radar data to support accurate weather forecasting and validate model predictions. Prepared METAR reports and organized flight weather folders in compliance with aviation meteorology standards, ensuring data quality for downstream use. The work involved ensuring recorded observations and dataset entries aligned with expected formats and integrity checks. • Collected and processed meteorological inputs from satellite imagery and radar data • Validated field observations against model predictions • Produced structured aviation weather reporting artifacts (METAR and flight folders) • Maintained dataset reliability through checks for correctness and consistency

2018 - 2018

Education

Work History