Data Labeling Analyst - Speach & Voice AI

Welocalize•New York, NY

About The Position

The Data Labeling Analyst will play a pivotal role in updating machine learning models and ensuring their efficacy. This role requires a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. The analyst will be responsible for updating training and test model databases, modifying guidelines, initiating model training, evaluating model performance, designing and developing datasets, handling data efficiently, annotating data accurately, conducting quality analysis, recognizing error patterns, delivering detailed reports, implementing quality control measures, utilizing data analysis techniques, and arbitrating discrepancies. The role also involves applying basic knowledge of natural language processing and linguistics to data processing tasks, ensuring linguistic accuracy. This role primarily focuses on English US data sets, but familiarity with multi-lingual data sets can be a plus.

Requirements

Foundational understanding of machine learning, data annotation, quality assurance, and natural language processing.
Familiarity with command-line tools and interfaces.
Strong analytical skills with the ability to identify patterns and anomalies.
Ability to work in a fast-paced, collaborative environment.
Excellent communication skills.

Nice To Haves

Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.
Familiarity with translation or multi-lingual data sets can be a plus for future projects.

Responsibilities

Update training and test model databases with new or amended synthetic textual and image data.
Modify and refine machine learning data creation, annotation, and rating guidelines.
Initiate model training processes using internal tools and command-line interfaces.
Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.
Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
Handle data efficiently, ensuring its integrity throughout the workflow.
Engage in data relevance tasks, ensuring data sets are aligned with project goals.
Annotate data accurately, ensuring it adheres to set guidelines.
Conduct manual quality analysis of model results.
Recognize error patterns and report anomalies for further investigation.
Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
Implement basic quality control measures and ensure the reliability of processed data.
Utilize intermediate data analysis techniques to extract insights and inform decision-making.
Arbitrate discrepancies effectively, ensuring consistent data quality.
Apply basic knowledge of natural language processing and linguistics to data processing tasks.
Ensure linguistic accuracy in all processed and annotated data.