Joseph O.

Key Skills

Software

Other

Top Subject Matter

Biological & Agricultural Sciences (Animal Science)

General analytics datasets (AI dataset preparation)

Legal Services & Contract Review

Top Data Types

Image

Audio

Text

Top Task Types

Evaluation/Rating

Transcription

Data Collection

Object Detection

Classification

Text Summarization

Question Answering

Bounding Box

Polygon

Polyline

Point/Key Point

Entity (NER) Classification

Freelancer Overview

Data Entry Specialist / Freelance Data Processor (AI-data QA & evaluation support). Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. Education includes Bachelor of Science, [University Name] (2027) and Professional Diploma in Data Analytics, TechCrush (2026). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

TechCrush Data Analytics Program & Personal Projects (AI dataset preparation)

OtherText

Built practical data analytics projects emphasizing data validation and quality assurance processes relevant to AI dataset preparation and annotation work. Transformed raw data into structured, reliable formats using SQL and advanced Excel cleaning techniques to make datasets label-ready. Leveraged Power BI and SQL to support ongoing dataset quality monitoring and preparation for AI-related labeling workflows. • Applied validation techniques and QA checks to improve dataset reliability for annotation. • Used Excel advanced functions and SQL querying to clean, structure, and manage datasets. • Produced visualization-ready datasets using Power BI dashboards for quality review. • Focused on converting messy inputs into consistent formats suitable for AI labeling pipelines.

2025 - Present

Data Entry Specialist / Freelance Data Processor (AI-data QA & evaluation support)

OtherText

Performed high-volume data entry with a strong focus on data validation, quality control, and error-free dataset preparation for downstream analytics and AI dataset use. Applied accuracy auditing, anomaly detection, and dataset organization workflows to support reliable labeling inputs. Assisted AI-support style tasks including LLM output evaluation, preference ranking, content moderation, and factuality checks to improve dataset quality. • Validated and cleaned raw records to maintain accuracy targets (98%+). • Identified edge cases and performed quality assurance before final dataset handoff. • Organized and categorized information for efficient retrieval and further analysis. • Used domain knowledge in biological and agricultural sciences to contextualize and improve labeling judgment.

2022 - Present

Education

Work History