Contractor Data Assistant

• Label historical conversation data: Use internal tools and clear guidelines to tag safety-relevant behaviors in AI data, including signs of harmful behavior.
• Query and organize datasets: Use basic SQL queries to extract and review relevant data for labeling and analysis.
• Work in Jupyter notebooks: Navigate and run your work within Jupyter notebooks to support traceability and collaboration with technical teams.
• Collaborate with cross-functional partners: Work alongside analysts, researchers, and engineers to refine labeling criteria and surface edge cases.
• Support labeling tool improvements: Provide structured feedback on labeling workflows to help improve future annotation tools and processes.

• Have a meticulous eye for detail and enjoy repetitive but high-stakes tasks where accuracy matters.
• Are organized and systematic, with a track record of following annotation guidelines and managing large volumes of information consistently.
• Are comfortable writing and interpreting basic SQL queries to retrieve and filter relevant data.
• Have hands-on experience using Jupyter notebooks to review data and document workflows.
• Are curious and technically inclined, with some exposure to Python or a willingness to learn.
• Communicate clearly and take initiative when something looks off or doesn’t align with the guidelines.
• Care about mental health, safety, and ethical tech—and want to support systems that take these seriously.

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