sues and risks through developing and iterating metrics systems. Meanwhile, the team also engages with cross functional teams in solving priority challenges by bringing in data-based insights.
Responsibilities:
- Refine label tree structure and develop and iterate SOPs for each label to improve machine learning in classifying customers' feedback intention;
- Ensure alignment and a good understanding of issue definitions and label iteration across regional teams;
- Improve Label precision and recall via improving labelling quality, SOP refinement, and clarifying edge cases to advance model training;
- Proactively explore new risk signals from consumers' feedback, incl. broadening feedback sources, and new risks;
- Proactively explore leveraging innovative solutions, e.g. multi-modal capability, AI tools to better classify customers' feedback intention or improve labelling efficiency.
Qualifications
Minimum Qualifications
- Bachelor's degree or above, with experience in policy operations or model labeling;
- Excellent written and verbal communication skills; ability to explain complex concepts to stakeholders;
- Has rigorous logical reasoning and structured thinking skills, can independently initiate and deliver plans with quality; Have good data analytical skills;
- Has quick learning capability, proactive and self-driven attitude, a sense of responsibility and teamwork spirits.
Preferred Qualifications:
- Candidates who have work experience in e-commerce, consulting or social media companies.
- Candidates who have work experience in governance are preferred;