For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
E

Emmanuel Akpan

Data Labeler & Annotator (Preference Ranking) – OuterLAI (Omni ELO Evaluation)

Nigeria flagAbak, Nigeria
Intermediate

Key Skills

Software

No software listed

Top Subject Matter

LLM Response Evaluation
Program Monitoring & Reporting
Community Health & Gender Data

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

ClassificationClassification

Freelancer Overview

Data Labeler & Annotator (Preference Ranking) – OuterLAI (Omni ELO Evaluation). Brings 6+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Multimango and NOMIS database. Education includes Master of Science, University of Uyo (2025) and Bachelor of Science, University of Uyo (2015). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Intermediate

Labeling Experience

Data Labeler & Annotator (Preference Ranking) – OuterLAI (Omni ELO Evaluation)

Text
Served as a Data Labeler & Annotator for the Omni ELO Evaluation project, specializing in preference ranking for large language model (LLM) outputs. Processed 3,500+ pairwise comparisons with high accuracy and flagged harmful or contradictory responses. Achieved 94% inter-annotator agreement through calibration and continuous rubric refinement. • Labeled over 3,500 comparison pairs with 95% consistency against gold standards. • Processed 70+ pairs per 6-hour shift, maintaining 98% daily throughput. • Proposed over 12 rubric clarifications, reducing disputes by 25%. • Flagged 150+ harmful/contradictory model responses, supporting safety evaluations.

Served as a Data Labeler & Annotator for the Omni ELO Evaluation project, specializing in preference ranking for large language model (LLM) outputs. Processed 3,500+ pairwise comparisons with high accuracy and flagged harmful or contradictory responses. Achieved 94% inter-annotator agreement through calibration and continuous rubric refinement. • Labeled over 3,500 comparison pairs with 95% consistency against gold standards. • Processed 70+ pairs per 6-hour shift, maintaining 98% daily throughput. • Proposed over 12 rubric clarifications, reducing disputes by 25%. • Flagged 150+ harmful/contradictory model responses, supporting safety evaluations.

2025 - 2026

Programs Officer – Youth Alive Foundation Africa (USAID/EU/Commonwealth)

TextClassification
Labeled and categorized over 500 narrative program reports and success stories for pattern analysis and documentation. Ensured 100% document filing accuracy and supported key data collection processes. Enabled efficient auditor access and improved reporting turnaround through effective data management. • Coded narrative reports for success pattern extraction. • Maintained detailed program documentation with zero errors. • Assisted in data-driven advocacy engagements. • Supported stakeholder data tracking and reporting improvement.

Labeled and categorized over 500 narrative program reports and success stories for pattern analysis and documentation. Ensured 100% document filing accuracy and supported key data collection processes. Enabled efficient auditor access and improved reporting turnaround through effective data management. • Coded narrative reports for success pattern extraction. • Maintained detailed program documentation with zero errors. • Assisted in data-driven advocacy engagements. • Supported stakeholder data tracking and reporting improvement.

2023 - 2024

Community System Strengthening & Gender Officer – Applicants Welfare & Development Centre (USAID-ICHSSA)

TextClassification
Annotated case finding and birth registration data from over 30 TBAs and 200+ child cases for program monitoring. Tracked gender session feedback using coded qualitative-to-quantitative methods. Coordinated referral flows to enhance dataset accuracy and reduce data loss. • Linked 95% of positive cases to care through annotation. • Maintained 99% data completeness in birth registration. • Monitored and coded 15+ gender norms sessions. • Reduced lost-to-follow-up in referral data by 18%.

Annotated case finding and birth registration data from over 30 TBAs and 200+ child cases for program monitoring. Tracked gender session feedback using coded qualitative-to-quantitative methods. Coordinated referral flows to enhance dataset accuracy and reduce data loss. • Linked 95% of positive cases to care through annotation. • Maintained 99% data completeness in birth registration. • Monitored and coded 15+ gender norms sessions. • Reduced lost-to-follow-up in referral data by 18%.

2021 - 2022

Monitoring & Evaluation Officer – Centre for Family Health Initiative (CDC-4GATES)

TextClassification
Managed and labeled over 6,000 orphan and vulnerable children records in NOMIS database, supporting quarterly data quality assessments. Identified and corrected hundreds of annotation errors to maintain data compliance. Trained staff and validated community-level data for reporting. • Ensured 98% data accuracy for sensitive program records. • Performed regular discrepancy tracking and correction. • Trained 25+ staff on accurate data labeling protocols. • Improved inter-rater reliability by 30%.

Managed and labeled over 6,000 orphan and vulnerable children records in NOMIS database, supporting quarterly data quality assessments. Identified and corrected hundreds of annotation errors to maintain data compliance. Trained staff and validated community-level data for reporting. • Ensured 98% data accuracy for sensitive program records. • Performed regular discrepancy tracking and correction. • Trained 25+ staff on accurate data labeling protocols. • Improved inter-rater reliability by 30%.

2019 - 2021

Monitoring & Evaluation Assistant – Centre for Family Health Initiative (CDC-ACHIEVE)

TextClassification
Assisted in labeling over 500 program volunteer-submitted data points, detecting discrepancies and supporting DQA efforts. Maintained complete NOMIS database records and ensured inventory tracking accuracy. Contributed to improved data cleanliness across multiple project sites. • Labeled and verified hundreds of volunteer data entries. • Identified and corrected 40+ data point discrepancies. • Ensured database completeness through inventory control. • Supported DQA to boost data quality by 15%.

Assisted in labeling over 500 program volunteer-submitted data points, detecting discrepancies and supporting DQA efforts. Maintained complete NOMIS database records and ensured inventory tracking accuracy. Contributed to improved data cleanliness across multiple project sites. • Labeled and verified hundreds of volunteer data entries. • Identified and corrected 40+ data point discrepancies. • Ensured database completeness through inventory control. • Supported DQA to boost data quality by 15%.

2019 - 2019

Education

U

University of Uyo

Bachelor of Science, Political Science and Public Administration

Bachelor of Science
2015 - 2015
U

University of Uyo

Master of Science, International Relations

Master of Science
2025

Work History

Y

Youth Alive Foundation Africa

Programs Officer

Abak
2023 - 2024
A

Applicants Welfare & Development Centre

Community System Strengthening & Gender Officer

Abak
2021 - 2022