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Francis Benard

Francis Benard

Data Analyst Data Quality & Annotation • MeriSKILL

Kenya flagnairobi, Kenya
$7.00/hrExpertMindriftMicro1Mercor

Key Skills

Software

MindriftMindrift
Micro1
MercorMercor
LabelImgLabelImg
iMeritiMerit
Data Annotation TechData Annotation Tech
ClickworkerClickworker
CloudFactoryCloudFactory
AppenAppen

Top Subject Matter

Machine Learning Data Annotation
Data Annotation for Institutional Analytics
Data Labeling for ML and Analytics

Top Data Types

TextText
ImageImage
VideoVideo

Top Task Types

ClassificationClassification
Object DetectionObject Detection
SegmentationSegmentation
Text GenerationText Generation
Text SummarizationText Summarization
TranscriptionTranscription
Data CollectionData Collection
Question AnsweringQuestion Answering

Freelancer Overview

Data Analyst Data Quality & Annotation • MeriSKILL. Core strengths include Tableau, Internal, and Proprietary Tooling. Education includes Bachelor of Science, South Eastern Kenya University (2021). AI-training focus includes data types such as Text and labeling workflows including Classification.

ExpertEnglishSwahili

Labeling Experience

Data Analyst Data Quality & Annotation • MeriSKILL

TextClassification
Annotated and validated over 10,000 data points using Python and Tableau, producing high-quality structured outputs for machine learning models. Developed and enforced standards for data labeling and classification to enhance analytics decision-making efficiency. Conducted quality assurance and integrity checks on a 50,000-record database, identifying and resolving more than 1,000 issues. • Enhanced annotation workflows to meet QA demands and institutional standards. • Reduced processing time by 25% through optimized data structuring. • Collaborated cross-functionally to improve the accuracy of labeled datasets. • Contributed to downstream ML model performance through data quality improvements.

Annotated and validated over 10,000 data points using Python and Tableau, producing high-quality structured outputs for machine learning models. Developed and enforced standards for data labeling and classification to enhance analytics decision-making efficiency. Conducted quality assurance and integrity checks on a 50,000-record database, identifying and resolving more than 1,000 issues. • Enhanced annotation workflows to meet QA demands and institutional standards. • Reduced processing time by 25% through optimized data structuring. • Collaborated cross-functionally to improve the accuracy of labeled datasets. • Contributed to downstream ML model performance through data quality improvements.

2023 - 2024

Remote Part-Time Data Analyst • Amazon

TextClassification
Reviewed and structured 2,500+ data points monthly for annotation readiness, while applying rigorous quality controls and validation for Amazon’s ML data pipeline. Improved data accuracy by 25% through systematic error detection, correction, and annotation preparation. Performed comprehensive data audits to reduce errors and increase data integrity for delivered datasets. • Supported pipeline from raw to labeled data for downstream AI models. • Applied annotation-ready standards and quality checks using internal Amazon tools. • Built analytics models using validated, labeled inputs for AI training purposes. • Ensured reliability and consistency of label outputs for global ML initiatives.

Reviewed and structured 2,500+ data points monthly for annotation readiness, while applying rigorous quality controls and validation for Amazon’s ML data pipeline. Improved data accuracy by 25% through systematic error detection, correction, and annotation preparation. Performed comprehensive data audits to reduce errors and increase data integrity for delivered datasets. • Supported pipeline from raw to labeled data for downstream AI models. • Applied annotation-ready standards and quality checks using internal Amazon tools. • Built analytics models using validated, labeled inputs for AI training purposes. • Ensured reliability and consistency of label outputs for global ML initiatives.

2022 - 2023

Data Science Intern • Bharat Intern

TextClassification
Generated data visualizations and structured outputs from large-scale datasets, improving accessibility and utilization of annotated data for analytics teams. Assisted in building a recommendation system with labeled training data, contributing to improved product sales for the organization. Supported end-to-end labeling and annotation tasks as part of machine learning support. • Labeled datasets for machine learning model development and evaluation. • Applied annotation standards to augment recommendation system performance. • Improved data accessibility by generating structured, labeled outputs. • Used Python and SQL for annotation, data cleaning, and validation workflows.

Generated data visualizations and structured outputs from large-scale datasets, improving accessibility and utilization of annotated data for analytics teams. Assisted in building a recommendation system with labeled training data, contributing to improved product sales for the organization. Supported end-to-end labeling and annotation tasks as part of machine learning support. • Labeled datasets for machine learning model development and evaluation. • Applied annotation standards to augment recommendation system performance. • Improved data accessibility by generating structured, labeled outputs. • Used Python and SQL for annotation, data cleaning, and validation workflows.

2022 - 2022

Junior Data Analyst Intern • UNHCR

TextClassification
Processed and structured 1.5 TB of raw data using Python, R, and SQL for downstream labeling solutions at UNHCR. Developed and implemented data cleaning, validation, and annotation workflows to improve processing accuracy and efficiency. Collaborated with cross-functional teams to apply data-driven labeling solutions and enhance operational outcomes. • Reduced labeling errors by 25% via QC-driven workflow improvements. • Increased data integrity by 30% after validation and annotation cycles. • Designed and applied structured labeling solutions in high-volume data environments. • Supported QA annotation processes aligned with institutional requirements.

Processed and structured 1.5 TB of raw data using Python, R, and SQL for downstream labeling solutions at UNHCR. Developed and implemented data cleaning, validation, and annotation workflows to improve processing accuracy and efficiency. Collaborated with cross-functional teams to apply data-driven labeling solutions and enhance operational outcomes. • Reduced labeling errors by 25% via QC-driven workflow improvements. • Increased data integrity by 30% after validation and annotation cycles. • Designed and applied structured labeling solutions in high-volume data environments. • Supported QA annotation processes aligned with institutional requirements.

2022 - 2022

Education

S

South Eastern Kenya University

Bachelor of Science, Public Health

Bachelor of Science
2021 - 2021

Work History

T

TURING

REMOTE DATA ANALYST

California
2025 - 2026
E

EDUSSON WRITERS

ACADEMIC WRITER

California
2021 - 2025