Mitchell A.

Key Skills

Software

Supervisely

Other

Top Subject Matter

AI training data (text classification and point/key-point annotation) for machine learning pipelines

EHR-derived structured patient data (schema validation and classification)

Legal Services & Contract Review

Top Data Types

Text

Document

Top Task Types

Classification

Entity (NER) Classification

Freelancer Overview

Independent AI Data Trainer & Labeler (Freelance). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Supervisely and Other. Education includes Bachelor of Science, Texas Wesleyan University (2025). AI-training focus includes data types such as Text, Medical, and DICOM and labeling workflows including Classification and Named Entity Recognition.

Labeling Experience

Independent AI Data Trainer & Labeler (Freelance)

SuperviselyTextClassificationEntity (NER) Classification

Performed text classification and annotation on large unstructured datasets using consistent labeling schemas and escalation for ambiguous cases. Completed point and key point labeling on structured datasets while maintaining accuracy standards above 99% for inter-rater reliability. Conducted quality assurance reviews on incoming batches to detect mislabeled entries, formatting issues, and guideline deviations before finalization. • Annotated 200–400 records per day in a remote, async workflow. • Flagged ambiguous cases for reviewer escalation and maintained label consistency. • Ran inter-rater reliability and QA checks across sessions. • Onboarded and trained two junior annotators, reducing early error rates.

2023 - Present

Administrative Data Processor (Remote)

OtherClassification

Handled classification and structured entry of patient data fields according to strict schema definitions, analogous to structured annotation workflows. Cross-referenced digital entries against source documents to catch and correct errors prior to committing records. Produced structured data exports and summary reports from the EHR system to support downstream consumption. • Tagged and categorized 100–150 records daily with schema validation. • Applied judgment to identify labeling edge cases during verification. • Maintained consistent output quality in a fast-paced remote environment. • Generated structured exports and reports from EHR records.

2021 - 2022

Education

Work History