Favour U.

Key Skills

Software

Other

Micro1

OneForma

Internal/Proprietary Tooling

Top Subject Matter

Finance & Trading (Forex, Indices, Funded Accounts)

Technology & Software Engineering

Community & Customer Support Operations

Top Data Types

Text

Document

Top Task Types

RLHF

Question Answering

Text Summarization

Evaluation/Rating

Prompt + Response Writing (SFT)

Freelancer Overview

Computer Engineering graduate with 5+ years of active trading experience specializing in NAS100 and forex indices, currently serving as Lead Moderator and quality reviewer for a community of 3,000+ traders at Funded Hive. My background combines deep finance domain expertise with strong technical skills in Python and JavaScript, making me well-suited for AI evaluation tasks that require genuine subject-matter knowledge — particularly in financial data annotation, RLHF preference ranking, and content quality review. I apply the same data-driven discipline and pattern recognition I use in trading to deliver consistent, high-accuracy outputs in structured review workflows. What sets me apart is the intersection of technical education, real-world market expertise, and hands-on experience managing quality at scale. Traders operate under pressure with zero margin for error — that mindset directly translates to the attention to detail, analytical rigor, and emotional discipline required for high-quality AI training data. I am proficient in Google Workspace, Notion, Excel, and AI productivity tools, with experience setting up and managing automated workflows. I am immediately available for freelance projects and bring a track record of structured documentation, rubric-based evaluation, and fast, reliable delivery.

Labeling Experience

Title Technical Community Support & AI-Assisted Workflow Evaluation

TextPrompt + Response Writing (SFT)

As Lead Moderator at Funded Hive, I regularly craft, evaluate, and refine responses to complex technical and trading-related queries submitted by community members. This involves assessing the quality of AI-assisted responses against human-generated answers, identifying gaps in accuracy, tone, and completeness, and rewriting or improving outputs to meet platform standards. I also integrate and configure AI tools and bots — including Ticket Tool, Carl-bot, and Dyno — reviewing their automated responses and adjusting prompts and parameters to improve output quality. This hands-on experience of comparing AI outputs against ideal human responses, then refining prompts to close the gap, directly mirrors Supervised Fine-Tuning (SFT) and prompt-response writing workflows used in AI model training.

2025 - Present

Financial Market Output Evaluation & Quality Review

TextEvaluation/Rating

As Lead Moderator at Funded Hive, I evaluate trader-generated content, platform responses, and support interactions daily across a community of 3,000+ active traders. This involves assessing outputs for accuracy, relevance, and quality against defined rubrics — flagging errors, resolving edge cases, and documenting decisions with clear reasoning. Drawing on 5+ years of active NAS100 and forex trading experience, I apply deep finance domain knowledge to distinguish correct from incorrect market information, identify misleading content, and provide structured feedback. This work closely mirrors RLHF evaluation and content quality annotation workflows in AI training environments.

2025 - Present

Financial Market Data Analysis & Pattern Recognition

TextClassification

Five years of independent trading in NAS100 and forex markets required systematic evaluation and classification of market data, price action patterns, and economic indicators. Each trade required structured documentation of entry/exit rationale, risk parameters, and outcome analysis — building a detailed personal database of annotated market scenarios. This involved classifying market conditions (trending, ranging, volatile), labeling chart patterns against defined criteria, and evaluating the quality of trade setups using consistent scoring rubrics. The discipline of maintaining accurate, bias-free records under real financial pressure developed strong habits in objective data classification, structured reasoning, and high-stakes decision-making.

2020 - Present

Education

Work History