G U.

Key Skills

Software

Scale AI

Top Subject Matter

Financial Compliance & Risk Analysis

Economics Domain Expertise

Accounting Domain Expertise

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

Classification

Text Generation

Text Summarization

RLHF

Red Teaming

Transcription

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Fine-tuning

Question Answering

Freelancer Overview

Specialist Quality Control Auditor. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI and Outlier AI. Education includes Master of Science, University of Birmingham (2024) and Bachelor of Science, University of Leicester (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Specialist Quality Control Auditor

Scale AIText

As a Specialist Quality Control Auditor at Scale AI, I audited MSc-to-PhD-level financial quantitative outputs for accuracy and adherence to AI evaluation standards. My responsibilities included reviewing final AI or contributor-generated outputs for instruction compliance and fact-checking. I also surfaced label inconsistencies in preference-ranking datasets to improve rubric design. • Conducted QC on deep learning model outputs in finance, economics, and accounting domains • Evaluated instruction-following, factual grounding, calculation, and assumption validity • Calibrated reliability on PRBench and preference-ranking datasets for LLM evaluation • Provided feedback to rubric design to ensure edge cases and label consistency

2025 - Present

Senior Reviewer

Text

As a Senior Reviewer at Outlier AI, I led end-to-end quality review of complex submissions related to AI evaluation. I calibrated and scored outputs involving STEM, economics, finance, and legal content for accuracy and rubric adherence. Additionally, I coached contributors to maintain consistent quality standards across a large remote team. • Performed daily multi-step evaluation and validation on AI or contributor-submitted annotations • Ensured consistent rubric interpretation across 200+ contributors in quantitative domains • Validated quantitative logic, assumption grounding, and evidentiary support in each reviewed piece • Reduced repeat quality failures through structured coaching and escalation of edge cases

2024 - 2025

Education

Work History