and the ability to collaborate across cross-functional teams. A keen eye for detail and a proactive mindset toward challenging existing processes and driving continuous improvement are essential.
Detailed responsibilities include:
- Ensure high-quality content benchmarking across BPO teams, support the setup, onboarding, and training of new BPO teams. Manage policy clarifications, calibrations, and arbitration processes. Analyze BPO team performance to identify knowledge gaps and systemic issues.
- Handle content labeling for specific queues based on cross-functional business requirements, analyze labeled content to identify trends and provide insights to project teams and independently manage quality evaluation initiatives, delivering actionable analytical insights.
- Train models using large datasets of labeled content to improve decision-making accuracy. Enhance model capabilities through iterative training and reinforcement learning, assist in data preparation, cleaning, and structuring for training purposes. Improve model accuracy by testing and fine-tuning, highlight the algorithm team with supporting examples for any potential gaps in LLM decision making draft, revise, and quality-check content to explore and enhance the synergy between human input and data in LLM training.
- Analyze moderation and labeling data from multiple queues to derive a process or market specific trend/correlation. Arrange supporting data points for impact analysis and solution planning.
- Custodian of all quality specific artifacts for the content moderation scope, generating creative solutions, including the use of technology and tools, to enhance the quality of both individual and team outputs.
Qualifications
Minimum Qualifications:
- Bachelor's degree in Business, Data Science, Computer Science, Information Technology, Communications, or a related field.
- Experienced in content quality management, product operations, or a related analytics role, preferably in tech, digital content, or platform moderation environments.
- Proficiency in data analysis and visualization tools such as Excel, Tableau, Power BI, or similar.
- Basic understanding of machine learning concepts and Large Language Models (LLMs).
- Strong ability to analyze complex datasets, identify patterns, and generate actionable insights.
Preferred Qualifications:
- Strong analytical skills with the ability to translate data into actionable insights, influence strategy, and drive impactful solutions.
- Solid understanding of machine learning principles, including model evaluation metrics and optimization techniques.
- Experience as RLHF (Reinforcement learning from human feedback) annotators for leading Al/LLM companies is strongly preferred.