Manager of Conversation Analysis
About the role
Position Summary
The Manager, Conversation Analysis leads a team of analysts and owns the labeling methodology, rubrics, and ground truth labeled data that power Authenticx AI models and generate insights for our clients. This leader is accountable for the engagement, accuracy, and throughput of the team, and for delivering labeling and insights mining initiatives on schedule. The role combines direct people management with deep methodological ownership and a client-facing presence. The right candidate develops analysts while holding them to clear performance standards, serves as the subject-matter expert in front of clients and cross-functional partners in Data Science, Prompt Engineering, Product, and Client Success, and actively advances how the function operates through innovation and focus on continuous improvement. This role blends people leadership, analytical rigor, and operational excellence in a fast-paced SaaS environment.
What You’ll Do
- Directly manage a team of analysts, including hiring, onboarding, performance reviews, career development, and day-to-day coaching
- Manage capacity, work prioritization, and timelines to meet project timelines
- Identify process improvements to increase efficiency, scalability, and reliability of labeling operations
- Develop rubrics and ground truth labeled data supporting AI model development, insights mining, and continuous improvement
- Ensure consistent application of rubrics through regular secondary reviews proactively addressing gaps while recognizing and developing high performers
- Partner with the AI and Data Science team to align labeling methodology with model development requirements while communicating progress, risks, and meaningful observations in the data.
- Serve as the Subject Matter Expert (SME) to customers and cross-functional partners in Data Science, Prompt Engineering, Product, and Client success related to our model development operating procedures
- Develop and maintain expert level knowledge in how labeled conversational data connects to model development and outcomes
- Serves as an escalation point collaborating with internal teams (Support, Product, Engineering, CS) to address any customer issues, ensuring swift and efficient resolution.
- Drive innovation and cast a vision for how we evolve our rubric design, labeling methodology, and insights mining and delivery
- Foster a culture of continuous improvement with strong performance, consistency, engagement