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Job Summary
Required Skills:
šData Annotation and Labeling: Extensive experience with data labeling tools and techniques, with the ability to create high-quality, structured datasets. šData Cleaning and Preprocessing: Strong understanding of data cleaning methods to prepare datasets for model training. You can handle structured and unstructured data formats. šAnalytical Skills and Quality Assurance: Ability to assess data quality and accuracy through quality assurance processes. You can troubleshoot and refine data to enhance model performance. šCollaboration and Communication: Strong communication skills to work with cross-functional teams and explain data requirements. Youāre detail-oriented and organized in managing datasets. šTechnical Skills: Proficiency in data manipulation using tools like Python or SQL. Familiarity with data labeling platforms (e.g., Labelbox, Amazon SageMaker Ground Truth, or Supervisely) is beneficial.
Educational Requirements:
šBachelorās or Masterās degree in Data Science, Computer Science, Information Management, or a related field. Equivalent experience in data annotation, AI training, or machine learning support may be considered. šCertifications in data science or machine learning fundamentals are advantageous but not required.