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Doutimiwei Ebenezer

Doutimiwei Ebenezer

Human-in-the-Loop Data Labeling & Model Evaluation Lead, PayGuard AI

Nigeria flagRemote, Nigeria
$40.00/hrIntermediate

Key Skills

Software

No software listed

Top Subject Matter

Fintech Fraud Detection
Regulatory Compliance & Risk Analysis
Legal Services & Contract Review

Top Data Types

TextText
Computer Code ProgrammingComputer Code Programming
DocumentDocument

Top Task Types

No task types listed

Freelancer Overview

Human-in-the-Loop Data Labeling & Model Evaluation Lead, PayGuard AI. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, Babcock University (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

IntermediateEnglish

Labeling Experience

Human-in-the-Loop Data Labeling & Model Evaluation Lead, PayGuard AI

Text
As Founder & Lead Engineer at PayGuard AI, I designed and implemented ML-powered fraud detection workflows with Human-in-the-Loop review for compliance and risk monitoring. I developed systems enabling manual and AI-assisted review of transactional data to identify fraudulent patterns and enable continuous retraining of deployed models. These workflows incorporated auto-retraining, 12-feature extraction and collaborative input to improve model accuracy and reduce manual review time. • Architected end-to-end AI-augmented labeling workflows for financial transaction data • Integrated periodic Human-in-the-Loop validation for ongoing model improvement • Built rule suggestion mechanisms utilizing review pattern analysis • Leveraged ML.NET in internal/proprietary platforms for SaaS compliance tools

As Founder & Lead Engineer at PayGuard AI, I designed and implemented ML-powered fraud detection workflows with Human-in-the-Loop review for compliance and risk monitoring. I developed systems enabling manual and AI-assisted review of transactional data to identify fraudulent patterns and enable continuous retraining of deployed models. These workflows incorporated auto-retraining, 12-feature extraction and collaborative input to improve model accuracy and reduce manual review time. • Architected end-to-end AI-augmented labeling workflows for financial transaction data • Integrated periodic Human-in-the-Loop validation for ongoing model improvement • Built rule suggestion mechanisms utilizing review pattern analysis • Leveraged ML.NET in internal/proprietary platforms for SaaS compliance tools

2026 - Present

Education

B

Babcock University

Bachelor of Science, Computer Science

Bachelor of Science
2019 - 2023

Work History

P

PayGuard AI

Founder and Lead Engineer

Remote
2026 - Present
A

AfterQuery Experts

Software Engineer - Testing & Evaluation

Remote
2025 - Present