Support data classification and taxonomy methods and standards, understand business, cooperate with data team.
Support analysis, identification and marking various data samples in storage, and ensure accuracy and recall rate.
Support R&D team to improve algorithm recognition and machine learning ability, analyze bad case of algorithm recommended data labels, put forward suggestions and basis for annotation/labelling, and participate in the discussion of algorithm model improvement solutions.
Deeply understand the business, investigate the data samples of each business line, and improve the classification standard of data labels and sample database.
Improve the data annotation operation process, optimize the label sampling and review mechanism, and improve the efficiency of manual standards.
Participate in the functional optimization design of the annotation platform.
Qualifications:
Bachelor's Degree in Computer Science or IT related discipline.
At least 1 year of working experience in research and development in testing, data analyst or DBA experience, familiar with all kinds of data samples in storage.
Excellent communication and analysis skills and good reasoning skills, able to quickly understand the business and judge the sample type according to the business attributes.
Willing to perform repetitive tasks effectively with a minimum of errors.
Knowledge and keen interest in artificial intelligence and machine learning.
