Data Annotator
Transcribed different pieces of Danish audio
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Data Annotator (QA) – Accenture / Finest People. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Appen. Education includes Associate of Professional Degree, Business Academy Aarhus (2025) and Exchange Semester, Amsterdam University of Applied Sciences (2024). AI-training focus includes data types such as Image, Text, and Audio and labeling workflows including Classification, Evaluation, and Rating.
Transcribed different pieces of Danish audio
As a Data Annotator (QA) at Accenture / Finest People, I labeled and reviewed datasets containing images, text, audio, and video for use in AI model training. I was responsible for validating, correcting, and ensuring data quality and relevance, contributing directly to the development of accurate machine learning systems. My work required attention to detail, a strong sense of data integrity, and effective collaboration with project stakeholders. • Annotated diverse data types to create high-quality training datasets • Evaluated and corrected data entries for accuracy and consistency • Provided feedback on annotation guidelines and quality assurance processes • Collaborated closely with data science teams to improve model outputs
As a Freelance Transcriber at Appen, I transcribed audio data to support AI improvement initiatives and machine learning projects. This role focused on converting spoken content into accurate text for use in training natural language processing models. I ensured the highest standards of accuracy and clarity throughout all transcriptions. • Listened carefully to diverse audio recordings • Transcribed spoken content with precise detail • Corrected transcription errors to improve data quality • Maintained strict confidentiality and adherence to data security protocols
Associate of Professional Degree, Computer Science
Exchange Semester, Mobile Development
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