Kelvin M.

Key Skills

Software

Other

Appen

Scale AI

Top Subject Matter

NLP (Sentiment Analysis and Entity Extraction)

Multimodal AI labeling (Segmentation, Text Classification, Medical Imaging)

AI training data labeling (Audio transcription

Top Data Types

Text

Image

Audio

Video

Document

Top Task Types

Segmentation

Transcription

Text Generation

Classification

Freelancer Overview

Data Annotation Analyst at DataBridge Corp., Nairobi (2021–2023). Brings 9+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other, Appen, and Internal. Education includes Bachelor of Science, University of Nairobi (2022) and Master of Business Administration, Strathmore University (2024). AI-training focus includes data types such as Text, Image, and Audio and labeling workflows including Entity (NER), Segmentation, and Transcription.

Labeling Experience

QA Reviewer / Senior Data Labeling Specialist at OpenTrain AI (2023–Present)

Text

During your OpenTrain AI contract work, you performed ongoing quality assurance to evaluate and calibrate annotation outputs across your labeling pipeline. You used real-time feedback and calibration sessions to keep label consistency within the team. Your QA activity directly supported high-accuracy dataset delivery for NLP, computer vision, and audio transcription tasks. • Performed QA review and evaluation of labeled samples • Delivered real-time feedback to a team of 12 labelers • Led calibration sessions to maintain consistency • Ensured accurate, model-ready outputs via continuous evaluation

2023 - Present

Senior Data Labeling Specialist at OpenTrain AI (2023–Present)

TextText Generation

As a Senior Data Labeling Specialist at OpenTrain AI (Contract), you labeled NLP training data including conversational and other text-based annotation tasks. You reviewed and calibrated labels to ensure consistency, using QA processes to keep accuracy above 97%. You also helped create and refine labeling guidelines by translating complex AI requirements into clear annotator instructions. • Annotated and reviewed 500–1,000+ text-based samples daily • Achieved 97%+ accuracy with guideline adherence • Contributed to guideline creation and annotator instruction writing • Escalated edge cases and ambiguous samples to project leads to reduce rework

2023 - Present

Senior Data Labeling Specialist at OpenTrain AI (2023–Present)

AudioTranscription

As a Senior Data Labeling Specialist at OpenTrain AI (Contract), you annotated and reviewed large volumes of audio transcription and other AI training data daily. You delivered 97%+ accuracy results while applying annotation guidelines consistently and escalating ambiguous samples as needed. You served as a QA reviewer for a team of 12 labelers, providing real-time feedback and calibration to maintain dataset consistency. • Annotated and reviewed 500–1,000+ samples daily across audio transcription • Achieved 97%+ accuracy through guideline-based labeling • Provided QA review and calibration for a 12-person labeling team • Identified and escalated edge cases and ambiguous samples to improve dataset quality

2023 - Present

Data Annotation Analyst at DataBridge Corp., Nairobi (2021–2023)

OtherVideoClassification

As a Data Annotation Analyst, you labeled video datasets to support machine learning training for enterprise clients. You ensured labeling quality while working across multiple task types such as classification and other model-relevant video annotation categories. You contributed to maintaining inter-rater consistency through audits and team best-practice adoption. • Labeled video datasets for ML training • Supported classification-oriented video labeling tasks • Maintained high precision across labeling categories • Participated in reliability audits to improve consistency

2021 - 2023

Data Annotation Analyst at DataBridge Corp., Nairobi (2021–2023)

OtherImageSegmentation

As a Data Annotation Analyst, you labeled image datasets to support computer vision model training for enterprise clients. You produced bounding box and other computer-vision annotations with consistently high quality, maintaining precision above 96% across task types. You contributed to a team-wide workflow by creating best-practice guidance and running inter-rater reliability audits. • Labeled image datasets for computer vision training • Produced bounding box annotations and related CV labeling outputs • Maintained precision above 96% across task types • Audited inter-rater reliability and improved Kappa scores from 0.82 to 0.94

2021 - 2023

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Education

Work History