Molly Morland
Oslo,Norway
Summary
Experienced professional in data annotation and evaluation, focused on delivering accurate and reliable datasets. Proficient in Norwegian and English, with a commitment to data quality in AI projects. History of successful collaboration with prominent data service companies in Norway, driving improvements in machine learning and linguistic data quality.
Overview
6
6
years of professional experience
6
6
years of post-secondary education
Work history
Data Quality Analyst
iMerit
Oslo, Norway
2024.06 - 2025.12
- Led QA for 50,000 annotated speech clips, ensuring 99.8% compliance with annotation standards.
- Reduced labeling inconsistencies by 35% through implementation of double-review pipelines.
- Identified and corrected 5,000+ machine-generated transcription errors, increasing ASR training accuracy by 21%.
- Conducted inter-annotator agreement checks, reaching 0.95 kappa consistency.
- Designed and deployed QC checklists, reducing post-submission corrections by 45%.
- Performed linguistic error audits on multilingual datasets, reducing accent misclassification by 18%.
- Cross-verified ASR output against human transcripts, cutting error rates by 32%.
- Improved dataset reliability by 20% by flagging and correcting mislabeled audio samples.
- Standardized transcription guidelines across teams, reducing guideline-related errors by 40%.
- Implemented weekly data validation reports, preventing recurring annotation mistakes.
Data Collection Specialist
Appen
Oslo, Norway
2022.01 - 2023.02
- Led quality review of 25,000 annotated clips, achieving 99% compliance with project guidelines.
- Detected and corrected annotation errors, improving dataset reliability by 30%.
- Conducted cross-verification of transcriptions with audio, reducing mislabeled data by 95%.
- Implemented double-review pipelines, ensuring consistent annotation standards across teams.
- Reported systemic labeling issues and proposed workflow changes, cutting annotation errors by 15%.
- Monitored inter-annotator agreement, achieving a 0.92 kappa score for dataset consistency.
- Audited multilingual transcription datasets for grammar, accent, and context accuracy.
- Designed QC checklists for annotators, reducing post-delivery corrections by 40%.
- Reviewed machine-generated labels, correcting errors to refine active learning models.
- Tracked annotation accuracy with weekly performance reports for team leads.
Data Annotator & Evaluator
Lionbridge
Oslo, Norway
2020.03 - 2021.02
- Annotated 35,000 speech clips with emotion, intent, and sentiment tags, improving virtual assistant contextual accuracy by 28%.
- Performed speaker diarization on 10,000 multi-party conversations, achieving 99% segmentation accuracy.
- Labeled 12,000 low-resource language utterances, enabling 4 new languages for ASR deployment.
- Tagged background noise levels across 9,000 audio files, enhancing model noise robustness by 23%.
- Classified prosody, intonation, and stress patterns in 15,000 clips for TTS model naturalness enhancement.
- Built 3 custom taxonomy frameworks for domain-specific audio (legal, medical, financial), improving data relevance by 30%.
- Segmented 500+ hours of continuous speech into utterances for ASR time-aligned datasets.
- Annotated code-switching speech samples, improving multilingual NLP models by 18%.
- Converted 25,000 annotated files into ASR-friendly formats, reducing preprocessing time by 40%.
- Managed demographic-balanced speech data collection (20,000 clips, 30+ accents) for fairness in AI models.
Education
Master of Science - Data Science
University of Oslo
Oslo 2017.09 - 2019.09
Bachelor of Science - Information Technology
Norwegian University of Science and Technology
Trondheim 2012.06 - 2016.05
Skills
- Audio Annotation & Labeling
- Speech Data Collection & Processing
- Speaker Diarization (multi-party conversations)
- Phonetic & Prosody Analysis (pitch, stress, intonation)
- Acoustic Feature Tagging (background noise, emotion, sentiment)
- Multilingual Data Annotation (low-resource & high-resource languages)
- Text Normalization for NLP pipelines
- Lexicon Building for Domain-Specific ASR (legal, medical, financial)
- Code-Switching & Disfluency Tagging
- ASR Data Formatting (Kaldi, Whisper, Wav2Vec-compatible)
Languages
Norwegian
Native
English
Fluent
Timeline
Data Quality Analyst
iMerit
2024.06 - 2025.12
Data Collection Specialist
Appen
2022.01 - 2023.02
Data Annotator & Evaluator
Lionbridge
2020.03 - 2021.02
Master of Science - Data Science
University of Oslo
2017.09 - 2019.09
Bachelor of Science - Information Technology
Norwegian University of Science and Technology
2012.06 - 2016.05