Idiopemipo S.

Key Skills

Software

No software listed

Top Subject Matter

Healthcare claims document processing (missing attachments classification)

Internal platform APIs and analytics data pipeline support

Top Data Types

Document

Video

Top Task Types

Classification

Freelancer Overview

Full Stack Engineer, Optum — automated document classification for claim attachment completeness. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include TensorFlow and AWS CloudWatch. Education includes Bachelor's Degree, University of Abuja (2025). AI-training focus includes data types such as Document and labeling workflows including Classification, Computer Programming, and Coding.

Labeling Experience

Full Stack Engineer - Optum

DocumentClassification

Built a real-time claims adjudication engine for the Optum Real platform using FastAPI and Pydantic for high-performance validation. Parsed X12 837 transaction sets and implemented Rust-backed validation to achieve sub-millisecond latency. Delivered payer workflow capabilities including error interception and policy search using hybrid retrieval. • Developed FastAPI services with Pydantic v2 • Implemented X12 EDI parsing and validation • Built hybrid search for payer policies using Python and Pinecone • Automated document classification and missing-attachment detection with Python and TensorFlow

2022 - Present

Full Stack Engineer, Optum — automated document classification for claim attachment completeness

DocumentClassification

Built an AI-driven document classification system that detects missing claim attachments as documents are uploaded in real time. The work focused on identifying and classifying document completeness issues for healthcare claim processing. This labeling-like automation supported downstream human review and improved operational throughput. • Parsed and validated incoming claim-related documents • Detected missing attachments during upload events • Used machine learning (TensorFlow) to automate document classification • Saved state agencies substantial staff time per year

2022 - Present

Software Development Engineer Intern, Amazon — APIs and monitoring enabling analytics data exchange

Document

Developed and integrated RESTful API capabilities that enabled data exchange between microservices and downstream analytics systems. While not explicitly described as annotation, the work supported data preparation and tracking for analytics pipelines. This contributed to the ability to structure and route data for later model training or evaluation. • Refactored internal modules to improve data pipeline performance • Built RESTful APIs for internal platform integrations • Integrated monitoring and logging for production visibility • Enabled smoother data exchange for analytics workflows

2018 - 2018

Education

Work History