Muiruri Njuguna

Key Skills

Software

Label Studio

Top Subject Matter

Economics Domain Expertise

Financial Markets

Market Analysis

Top Data Types

Text

Top Task Types

RLHF

Classification

Freelancer Overview

AI Economics Annotation Consultant. Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, Internal, and Proprietary Tooling. Education includes Bachelor of Science, San Francisco State University (2013). AI-training focus includes data types such as Text and labeling workflows including RLHF and Classification.

Labeling Experience

AI Economics Annotation Consultant

Label StudioTextRLHF

As an AI Economics Annotation Consultant, I annotated, evaluated, and labeled economics content for AI training datasets. I developed structured annotation guidelines and labeling taxonomies for economic terminology, entity classification, and sentiment tagging. I ensured high data integrity by conducting QA and advising on best practices for ambiguous or subjective labeling situations. • Achieved >98% inter-annotator agreement across 500+ economics labeling tasks. • Applied expertise in RLHF-style response ranking and preference labeling for economic outputs. • Authored annotation guidelines and taxonomies for economic datasets. • Utilized tools such as Label Studio, Scale AI, and Surge AI for annotation and quality control.

As an AI Economics Annotation Consultant, I annotated, evaluated, and labeled economics content for AI training datasets. I developed structured annotation guidelines and labeling taxonomies for economic terminology, entity classification, and sentiment tagging. I ensured high data integrity by conducting QA and advising on best practices for ambiguous or subjective labeling situations. • Achieved >98% inter-annotator agreement across 500+ economics labeling tasks. • Applied expertise in RLHF-style response ranking and preference labeling for economic outputs. • Authored annotation guidelines and taxonomies for economic datasets. • Utilized tools such as Label Studio, Scale AI, and Surge AI for annotation and quality control.

2022 - Present

Senior Economic Analyst (AI Data Labeling Emphasis)

TextClassification

As a Senior Economic Analyst at Salesforce, I labeled, classified, and structured economic data for numerous projects supporting AI annotation workflows. I designed training programs on economic data interpretation, contributing to reproducible annotation guidance. I embedded high quality standards for predictive models, supporting collaborative data labeling and documentation. • Completed labeling and classification tasks for 100+ annual economic data projects. • Developed structured annotation outputs for cross-functional data teams. • Delivered formal training on data classification for annotation teams. • Maintained quality assurance practices to reduce inter-rater disagreement.

As a Senior Economic Analyst at Salesforce, I labeled, classified, and structured economic data for numerous projects supporting AI annotation workflows. I designed training programs on economic data interpretation, contributing to reproducible annotation guidance. I embedded high quality standards for predictive models, supporting collaborative data labeling and documentation. • Completed labeling and classification tasks for 100+ annual economic data projects. • Developed structured annotation outputs for cross-functional data teams. • Delivered formal training on data classification for annotation teams. • Maintained quality assurance practices to reduce inter-rater disagreement.

2018 - 2022

Economic Research Specialist (Data Labeling for ML)

TextClassification

As an Economic Research Specialist, I curated and labeled large-scale economic datasets for market analysis. I applied systematic categorization to ensure data was clean, structured, and suitable for AI/ML training. My work involved classification of both qualitative and quantitative data for economic forecasting models. • Led classification tasks for diverse economic variables and datasets. • Standardized data collection and labeling practices across research initiatives. • Delivered training-ready data for economic and AI model pipelines. • Supported inter-team calibration for labeled data quality.

As an Economic Research Specialist, I curated and labeled large-scale economic datasets for market analysis. I applied systematic categorization to ensure data was clean, structured, and suitable for AI/ML training. My work involved classification of both qualitative and quantitative data for economic forecasting models. • Led classification tasks for diverse economic variables and datasets. • Standardized data collection and labeling practices across research initiatives. • Delivered training-ready data for economic and AI model pipelines. • Supported inter-team calibration for labeled data quality.

2013 - 2018

Economic Research Coordinator (Structured Data Labeling)

TextClassification

As an Economic Research Coordinator, I organized and structured economic datasets using standardized labeling frameworks. My responsibilities included ensuring consistency and completeness in labeled data, enhancing its use for downstream analytics and AI model evaluation. I also contributed to QA for market analysis reports, focusing on accuracy and data reliability. • Applied structured frameworks for economic data labeling and categorization. • Enhanced usability of labeled datasets for analytical workflows. • Supported QA of annotated data for market research deliverables. • Contributed to data preparation for AI model evaluation tasks.

As an Economic Research Coordinator, I organized and structured economic datasets using standardized labeling frameworks. My responsibilities included ensuring consistency and completeness in labeled data, enhancing its use for downstream analytics and AI model evaluation. I also contributed to QA for market analysis reports, focusing on accuracy and data reliability. • Applied structured frameworks for economic data labeling and categorization. • Enhanced usability of labeled datasets for analytical workflows. • Supported QA of annotated data for market research deliverables. • Contributed to data preparation for AI model evaluation tasks.

2010 - 2013

Education

Work History