Awajima E.

Key Skills

Software

Other

Top Subject Matter

Insurance claims processing and insurance adjuster productivity

Applied data science and machine learning foundations

E - Commerce

Top Data Types

Document

Image

Text

Top Task Types

Function Calling

Data Collection

Object Detection

Evaluation/Rating

Computer Programming/Coding

Freelancer Overview

Lead Developer / Consultant — Insurance Adjuster AI Claims Platform. Brings 20+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Certificate, Udemy.com and N/A, WorldQuant University (2020). AI-training focus includes data types such as Document and labeling workflows including Function Calling and Data Collection.

Labeling Experience

Lead Developer / Consultant — Insurance Adjuster AI Claims Platform

DocumentFunction Calling

Built and integrated multi-AI agent workflows for an insurance claims processing platform, including controlled access to training documents used by the AI agents. Implemented per-organization encrypted AI API keys to secure organization-specific AI operations and ensure only authorized document context was used for downstream responses. Focused on enabling AI productivity for insurance adjusters rather than manual data labeling, with document access controls as the core training-data handling mechanism. • Managed multi-tenant SaaS workflows for AI agent execution across organizations • Enforced training-document access controls for per-organization confidentiality • Secured AI agent connectivity using AES-256-GCM encrypted API keys • Supported claims experts with a consulting framework alongside the AI system

2024 - Present

Applied Data Science — WorldQuant University (coursework)

OtherDocumentData Collection

Completed Applied Data Science and related coursework that supports AI training and data-centric workflows. Developed practical understanding of statistical analysis and machine learning methods that are used to prepare datasets and support model training. Used a Python-based learning stack as part of the training workflow for AI model development. • Applied statistical and machine learning concepts to data-centric projects • Used Python and Jupyter for experimenting with analysis workflows • Covered scientific computing concepts relevant to model training pipelines • Strengthened foundation for building AI training datasets and preparing inputs

2020 - 2020

Education

Work History