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Text
Audio
Computer Code Programming
Transcription
Evaluation/Rating
SegmentationAd Rater. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, University of Applied Sciences (2025) and Higher Education Entrance Qualification (Abitur), N/A (2025). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Transcription.
labeling, tagging, or outlining objects within images to create high-quality training data for machine learning and computer vision models
As a Transcriptionist, I converted spoken audio content into accurate written transcripts. My responsibilities included careful listening, precise typing, and reviewing text for quality assurance. These transcripts supported AI systems in improving Natural Language Processing capabilities. • Listened to audio files and produced verbatim transcripts • Edited and proofread text to maintain high accuracy and consistency • Labeled and segmented speech, speaker turns, and relevant audio events • Contributed to datasets used for training speech recognition AI models
As an Ad Rater, I evaluated online advertisements for quality and relevance based on detailed guidelines. My work contributed to refining AI algorithms for serving more accurate and useful ad content. I consistently maintained high accuracy and impartiality in my assessments. • Followed specific project guidelines to evaluate textual and visual ad content • Provided structured feedback on ad accuracy, usefulness, and target audience • Assisted in training AI systems to better filter and deliver advertisements • Ensured detailed documentation of evaluation results for quality assurance purposes
As a Translator, I performed English-German and Japanese-German translation and localization. This involved annotating and adapting texts to target cultural and linguistic norms while following strict project guidelines. My efforts aided multilingual AI models in understanding and generating human-like translations. • Translated diverse content types with high accuracy and attention to context • Annotated errors, ambiguities, and idiomatic expressions in both languages • Reviewed and evaluated machine-generated translations for quality improvement • Supported datasets for Natural Language and Language Model training
Higher Education Entrance Qualification (Abitur), General Education
Bachelor of Science, Science
Software Developer
Transcriptionist
