Data specialist (remote)

Role: Data Specialist (Remote) Location: Remote (Work from Anywhere)

Role Overview:

We are hiring for one of our clients, seeking a Human Data Manager, New Grad to work on a full-time basis. The role involves maintaining high-quality datasets used in AI model training and evaluation, ensuring accuracy and relevance of labeled information. Candidates will assist in refining data pipelines and improving annotation processes for machine learning applications.

Key Responsibilities:

Review and validate human-labeled data to ensure consistency and accuracy for AI training datasets Identify and resolve discrepancies in data annotations by cross-referencing source materials and guidelines Collaborate with cross-functional teams to refine annotation guidelines and improve data quality standards Monitor and report on data labeling performance metrics to track progress and identify trends Assist in documenting processes and maintaining records of data sources, labeling rules, and quality checks

Required Skills & Qualifications:

Experience with data annotation, labeling, or quality assurance processes is preferred Familiarity with basic data validation techniques and attention to detail in reviewing datasets Ability to follow structured guidelines and maintain consistency in data handling tasks Basic understanding of AI/ML concepts and their dependence on high-quality training data is beneficial Proficiency in using spreadsheets or data management tools to track and organize information

More About the Opportunity:

This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, contributing to the development of reliable AI systems through precise data management. The position provides exposure to real-world applications of data in machine learning workflows.

Equal Opportunity Employer:

We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.

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