Demilade A.

Key Skills

Software

Don't disclose

Google Cloud Vertex AI

Top Subject Matter

Social media video claims moderation (TikTok).

Urban mobility analytics (NYC TLC taxi fares) and experimentation.

Time-series/forecasting for national parks visitation and overcrowding mitigation.

Top Data Types

Video

Document

Top Task Types

Classification

Freelancer Overview

TikTok Video Claims Classification Model – Google Data Analytics Capstone. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Google Cloud Vertex AI. Education includes Bachelor of Science, Covenant University (2027) and Certificate, Brightchamp (2022). AI-training focus includes data types such as Video, Computer Code, and Programming and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

Data Analyst Intern (Project-Based Capstone) - Google Data Analytics Project

VideoClassification

Completed an end-to-end video analytics classification capstone using Python and statistical testing. Analyzed 19k+ videos to compute mean view metrics and compare claims versus opinions for moderation insights. Applied hypothesis testing on verified versus unverified status to support a data-driven recommendation for user behavior insights. • Processed and analyzed large video datasets in Python/NumPy • Computed and balanced claims/opinion statistics for moderation • Ran hypothesis tests to evaluate verified status differences • Produced recommendations based on p-value outcomes and model implications

2025 - 2025

National Parks Visitation Forecasting Model – Google Data Analytics Project

Don't discloseDocumentClassification

Developed a forecasting model for national parks visitation using large-scale visit records. Engineered predictive features from aggregated visitation data and used machine learning to estimate outcomes for multiple parks. Created visualizations and a mitigation-focused summary targeting overcrowding levels. • Engineered features from 312M visit data (e.g., temperature score). • Built an XGBoost model with double recall improvements using a random forest approach. • Evaluated accuracy goals for the top 8 parks and summarized performance. • Produced overcrowding mitigation visualizations and reporting.

2025 - 2025

NYC TLC Taxi Fare Prediction & A/B Testing – Google Data Analytics Project

Google Cloud Vertex AI

Performed data-driven analysis for a taxi fare prediction workflow and an A/B testing study on payment types. Conducted cleaning and exploratory analysis on a large tabular dataset to support regression prototype development. Evaluated differences between experimental groups using summary findings suitable for business decision-making. • Conducted EDA on 200k+ records and cleaned outliers in total_amount and trip_distance. • Built a regression prototype for fare prediction modeling. • Ran an A/B test comparing credit card versus cash payment fare outcomes. • Prepared an executive summary to support revenue strategy decisions.

2025 - 2025

TikTok Video Claims Classification Model – Google Data Analytics Capstone

Don't discloseVideoClassification

Built and evaluated a TikTok video claims moderation classification model using large-scale video data. Computed statistical baselines to compare verified versus unverified distributions and supported model decisions with hypothesis testing. Used label-derived measures (claims vs. opinions) to guide regression-based insight generation for user behavior. • Analyzed 19k+ videos and quantified mean views for claims/opinions. • Ran hypothesis testing on verified status to identify statistically significant differences. • Engineered balanced claim/opinion signals to improve moderation model behavior. • Produced recommendations tied to regression insights for downstream analysis.

2025 - 2025

Education

Work History