AI UX Conversational Analyst Intern
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Job Description
AI UX Conversational Analyst Intern at Rocket Lawyer enhancing AI-driven legal services through user research and analysis. Work with cross-functional teams to improve user experience and conversational patterns.
Responsibilities:
- Transcript Analysis: Review anonymized chat logs to identify where Rocket Copilot "hallucinates" or where users feel frustrated by legal complexity.
- Research Design: Work with product, design, data, legal, and engineering teams to establish user-value focused research questions to assess user value and value gaps in our products.
- User Research Support: Help coordinate and take notes during usability sessions where real users interact with our AI agents.
- Quality Audit: Maintain a "Library of Truth"—documenting the best-performing conversational patterns to be reused across the platform.
- Outcome focused: Focusing on producing insights on which conversations lead to conversion and engagement
- Prompt Testing: Run "A/B tests" on different AI prompts to see which version provides the most helpful, legally safe, and engaging response.
- Style Guide/ Rubric: Based on your insights during this internship, create a style guide on voice and tone to which users respond better
Requirements:
- Recent Grad: Research focused Masters degree in Linguistics, Cognitive Science, or a similar field.
- Analytical Curiosity: You love digging into data to find the "Why" behind a user's behavior.
- Writing Skills: You can take a 10-sentence text and turn it into a 2-sentence conversational response without losing the meaning.
- Research Background: You have undertaken previous research projects in different areas. Cataloging experience is a plus.
- Some familiarity with LLMs (like Gemini) and a desire to learn professional tools
- Mission-Aligned: You believe that everyone, regardless of their bank account, should have access to legal protection
- Language/ Translation Skills: You can understand the nuances in analyzing the style, tone and language used by Copilot, and identify where users respond positively.
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