Brian Mwaura

Statistics graduate (BSc, Laikipia University) with direct, hands on experience evaluating and authoring high quality reference content for AI model training. At Innodata and Pareto AI, produced and scored structured explanations, Q&A pairs, and step by step solutions against strict accuracy and quality guidelines, the same discipline required to write and review golden responses for advanced mathematics prompts. Strong quantitative foundation from formal statistics training (probability, regression, statistical inference, time series, and modeling), combined with a track record of translating complex, technical material into clear, structured, and precise written explanations.

Comfortable working independently in a distributed, output based, deadline driven remote environment.

AI Evaluation Analyst at Innodata (2025-11 – 2026-05)

• Created and annotated high quality AI training datasets, including prompts, Q&A pairs, and structured explanations, following strict quality guidelines to support model accuracy improvements.
• Reviewed and scored AI generated outputs for accuracy, logical coherence, and policy compliance, identifying errors, gaps, and inconsistencies across multiple model iterations.
• Implemented QA feedback cycles and collaborated with a cross functional, distributed team to maintain consistent quality and delivery standards.

LLM Evaluation Contributor at Pareto AI (2025-09 – 2026-04)

• Evaluated large language model performance through structured testing, contributing findings that informed iterative model improvement.
• Translated complex interaction flows and edge cases into structured, reproducible test scripts to support scalable evaluation pipelines.
• Maintained detailed, precise documentation of test cases and findings to ensure evaluation reliability and consistency.

Freelance Data Analyst at Self Employed (2025-01 – 2026-04)

• Delivered end to end quantitative analysis for multiple clients, covering statistical modeling, pricing optimization, and predictive analysis.
• Built structured, well documented analytical reports and dashboards to communicate quantitative findings clearly to non technical stakeholders.

Applied Data Science Apprentice at WorldQuant University (2024-12 – 2025-06)

• Completed 8 end to end data science projects spanning classification, regression, clustering, and time series forecasting.
• Developed and validated statistical and predictive models, presenting findings through structured, well reasoned analytical write ups.

Bachelor of Science in Statistics – Laikipia University (2018-09 – 2022-12)