Zweli Khumalo

Key Skills

Software

Labelbox

Other

Top Subject Matter

Quantitative Finance

Quantitative Finance and Financial Engineering

Legal Services & Contract Review

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

Prompt + Response Writing (SFT)

Freelancer Overview

AI Expert Reviewer | Quantitative Finance | Alignerr / Labelbox, USA. Brings 15+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox and Other. Education includes Master of Science, WorldQuant University (2022) and Professional Certificate, Columbia University (2022). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

AI Expert Reviewer | Quantitative Finance | Alignerr / Labelbox, USA

LabelboxText

As an AI expert reviewer for Alignerr and Labelbox, I evaluated quantitative finance submissions for four projects using structured rubrics. I assessed derivative pricing, risk analytics, portfolio optimization, and time-series projects for technical accuracy and industry standards. I contributed to rubric development and refined evaluation criteria to improve AI model training quality. • Reviewed AI outputs and quantitative model implementations across multiple finance domains. • Provided expert feedback and ensured adherence to best practices in model development and assessment. • Participated in iterative rubric refinement for consistent evaluation outcomes. • Collaborated with both technical and non-technical teams to coordinate review standards.

As an AI expert reviewer for Alignerr and Labelbox, I evaluated quantitative finance submissions for four projects using structured rubrics. I assessed derivative pricing, risk analytics, portfolio optimization, and time-series projects for technical accuracy and industry standards. I contributed to rubric development and refined evaluation criteria to improve AI model training quality. • Reviewed AI outputs and quantitative model implementations across multiple finance domains. • Provided expert feedback and ensured adherence to best practices in model development and assessment. • Participated in iterative rubric refinement for consistent evaluation outcomes. • Collaborated with both technical and non-technical teams to coordinate review standards.

2025 - Present

AI Training Domain Expert | Quantitative Finance | Pareto AI, USA

OtherPrompt Response Writing SFT

I served as an AI training domain expert for Pareto AI, engineering and fine-tuning prompts for language models in quantitative finance. I developed, validated, and optimized Python code generated by AI models for various financial modeling tasks. I led initiatives to develop training rubrics and ensure professional standards in output quality. • Wrote and reviewed LLM prompts and expected responses specific to quantitative finance tasks. • Optimized and evaluated AI-generated Python code for correctness and computational efficiency. • Designed and refined standardized training rubrics and guidelines for model training. • Led training programs to build internal AI model proficiency in finance applications.

I served as an AI training domain expert for Pareto AI, engineering and fine-tuning prompts for language models in quantitative finance. I developed, validated, and optimized Python code generated by AI models for various financial modeling tasks. I led initiatives to develop training rubrics and ensure professional standards in output quality. • Wrote and reviewed LLM prompts and expected responses specific to quantitative finance tasks. • Optimized and evaluated AI-generated Python code for correctness and computational efficiency. • Designed and refined standardized training rubrics and guidelines for model training. • Led training programs to build internal AI model proficiency in finance applications.

2025 - 2025

Education

Work History