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Noklem Naanpet

Noklem Naanpet

Programme Officer – Data Labeling and Validation

Nigeria flagJos, Nigeria
$10.00/hrIntermediateClickworkerAppenRemotasks

Key Skills

Software

ClickworkerClickworker
AppenAppen
RemotasksRemotasks
Scale AIScale AI
TolokaToloka
LabelboxLabelbox

Top Subject Matter

Health program data
Social research and evaluation
Training and economic empowerment data

Top Data Types

DocumentDocument
TextText
ImageImage

Top Task Types

ClassificationClassification
Object DetectionObject Detection
Text GenerationText Generation
Question AnsweringQuestion Answering
Text SummarizationText Summarization
Fine-tuningFine-tuning

Freelancer Overview

Programme Officer – Data Labeling and Validation. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Microsoft Excel. Education includes a Bachelor of Science in Economics Education, Usmanu Danfodiyo University, Sokoto. AI-training focus includes data types such as Document and labeling workflows, including Classification. I have hands-on experience working with both structured and unstructured data through my background in monitoring & evaluation, research, and program implementation. While my roles were not titled “data annotator,” they involved core data labeling tasks such as data categorization, validation, and quality control. One key area of experience is survey and field data processing. I worked on projects where I collected and handled over 500+ survey responses, organizing and categorizing qualitative and quantitative data into structured formats for analysis. This involved tagging responses, cleaning datasets, and ensuring consistency and accuracy before reporting. I have also worked extensively with structured datasets using Excel and Google Sheets, where I performed data cleaning, validation, and classification. I regularly identified inconsistencies, corrected errors, and maintained high data accuracy (typically 98%+), which aligns closely with data annotation quality standards. In addition, I supported research and reporting activities by labeling qualitative data from interviews and focus group discussions. This included grouping responses into themes, tagging key insights, and preparing structured outputs for decision-making. I am currently expanding my expertise into AI-specific annotation tools and workflows, including image and text annotation, and I am familiar with annotation guidelines, quality assurance processes, and task-based labeling environments. Overall, my experience has equipped me with strong attention to detail, consistency in applying guidelines, and the ability to work efficiently with large datasets, skills that directly translate into high-quality data labeling and annotation work.

IntermediateEnglishHausa

Labeling Experience

Programme Officer – Data Labeling and Validation

DocumentClassification
As a Programme Officer, I performed regular data labeling tasks, including categorization and verification of structured datasets in Excel. I maintained high accuracy in data validation, ensuring that data entries were reliably classified for organizational reporting. Quality assurance measures were applied to improve data reliability and consistency. • Consistently processed and validated 300+ data entries monthly • Applied structured classification guidelines to survey and indicator data • Used Excel for managing, tracking, and updating datasets • Improved dataset consistency through quality assurance checks

As a Programme Officer, I performed regular data labeling tasks, including categorization and verification of structured datasets in Excel. I maintained high accuracy in data validation, ensuring that data entries were reliably classified for organizational reporting. Quality assurance measures were applied to improve data reliability and consistency. • Consistently processed and validated 300+ data entries monthly • Applied structured classification guidelines to survey and indicator data • Used Excel for managing, tracking, and updating datasets • Improved dataset consistency through quality assurance checks

2023 - 2024

Economic Empowerment Trainer – Dataset Annotation

DocumentClassification
As an Economic Empowerment Trainer, I managed and annotated participant datasets for program evaluation. Classification and analysis of training data were crucial for monitoring outcomes and reporting insights. Data labeling supported evidence-based evaluations and program adjustments. • Maintained and annotated program participant data • Classified entries to aid systematic reporting • Used Excel to support data analysis for evaluations • Enhanced data integrity through careful management

As an Economic Empowerment Trainer, I managed and annotated participant datasets for program evaluation. Classification and analysis of training data were crucial for monitoring outcomes and reporting insights. Data labeling supported evidence-based evaluations and program adjustments. • Maintained and annotated program participant data • Classified entries to aid systematic reporting • Used Excel to support data analysis for evaluations • Enhanced data integrity through careful management

2021 - 2022

Programme Officer (GBV/SEA) – Data Structuring and Validation

DocumentClassification
In the Programme Officer (GBV/SEA) role, I organized, validated, and classified datasets for research and reporting purposes. Data labeling enabled structured survey data for downstream analysis and ensured quality control. Rigorous validation processes improved data usefulness for research outputs. • Prepared datasets for gender-based violence and abuse research • Structured and classified survey results in Excel • Implemented quality checks on all labeled data • Supported research teams with accurate labeled information

In the Programme Officer (GBV/SEA) role, I organized, validated, and classified datasets for research and reporting purposes. Data labeling enabled structured survey data for downstream analysis and ensured quality control. Rigorous validation processes improved data usefulness for research outputs. • Prepared datasets for gender-based violence and abuse research • Structured and classified survey results in Excel • Implemented quality checks on all labeled data • Supported research teams with accurate labeled information

2019 - 2021

Girls Empowerment & Mentoring Officer – Data Categorization

DocumentClassification
As Girls Empowerment & Mentoring Officer for the GEMS Project, I collected, labeled, and categorized participant data. Structured annotation of program and mentorship records facilitated streamlined program monitoring. Accurate labeling was essential for tracking engagement and performance metrics. • Categorized data for 200+ program participants • Maintained labeled records for ongoing analysis • Used Excel for dataset management and updates • Contributed to consistent program tracking through annotation

As Girls Empowerment & Mentoring Officer for the GEMS Project, I collected, labeled, and categorized participant data. Structured annotation of program and mentorship records facilitated streamlined program monitoring. Accurate labeling was essential for tracking engagement and performance metrics. • Categorized data for 200+ program participants • Maintained labeled records for ongoing analysis • Used Excel for dataset management and updates • Contributed to consistent program tracking through annotation

2016 - 2020

Monitoring & Evaluation / Data Support – Survey Labeling

DocumentClassification
In my Monitoring & Evaluation / Data Support position, I executed data labeling for both qualitative and quantitative research datasets. Classification and categorization activities were performed to structure survey responses for analysis and report generation. The labeled data enabled programmatic insights and outcome tracking. • Processed and validated 500+ survey responses • Conducted qualitative/quantitative data classification for research use • Ensured data consistency and accuracy through meticulous categorization • Supported reporting with structured output from labeled data

In my Monitoring & Evaluation / Data Support position, I executed data labeling for both qualitative and quantitative research datasets. Classification and categorization activities were performed to structure survey responses for analysis and report generation. The labeled data enabled programmatic insights and outcome tracking. • Processed and validated 500+ survey responses • Conducted qualitative/quantitative data classification for research use • Ensured data consistency and accuracy through meticulous categorization • Supported reporting with structured output from labeled data

Not specified

Education

U

Usmanu Danfodiyo University, Sokoto

Bachelor of Science in Education, Economics

Bachelor of Science in Education
Not specified

Work History

S

Society for Family Health

Programme Officer

Jos
2023 - 2024
W

Women for Women International

Economic Empowerment Trainer

Jos
2021 - 2022