Data Coach

Core Responsibilities

• Join the live session at least 15 minutes early and be active throughout.
• Support the LI by:
• Monitoring and responding to participant questions in chat in real time.
• Facilitating breakout rooms and ensuring groups understand tasks, stay on track, and complete activities.
• Helping learners go beyond surface-level answers (clarify use cases, strengthen prompts, encourage peer learning).
• Teach validation and healthy skepticism: how to sanity-check AI-generated interpretations.
• Flag urgent issues, trends, or blockers to Correlation One staff (via internal Slack channel).
• Step in to support session continuity if the LI encounters technical issues (as needed).
• Host 30-minute office hours sessions as requested/scheduled by assigned teams.
• Support learner project questions, tooling issues, and concept clarification.
• Provide support and feedback on deliverables.
• Escalate recurring issues or trends to the C1 team.
• Review team submissions.
• Provide detailed, actionable feedback.
• Ensure feedback is delivered within 72 hours of submission.
• Report on team progress to C1 team weekly.

Non-Live Support & Communication

• Respond to participant questions within 24 hours.
• Attend weekly C1 team sync.
• Log hours weekly in coaches workbook.

Deliverables Review

• Review team submissions.
• Provide detailed, actionable feedback.
• Ensure feedback is delivered within 72 hours of submission.
• Report on team progress to C1 team weekly.

Who You Are

• A native Spanish speaker with professional fluency in English.
• A hands-on data practitioner with experience applying analytics to real business challenges.
• A hands-on user of generative AI in a real commercial or analytics job — not just familiar with it, but able to show a workflow they've actually improved with it.
• Comfortable working with commercial, sales, marketing, and cross-functional teams.
• Able to translate data outputs into practical, actionable insights.
• Skilled at navigating dashboards, tools, and data models in live sessions.
• Skilled at guiding participants through exercises and reinforcing key learning points.
• Adaptable, and responsive to different learning styles and levels of data maturity.
• Organized and detail-oriented, ensuring smooth session support.
• Professional and collaborative, fostering a constructive and engaging learning environment.
• Familiar with enterprise AI governance and data-confidentiality norms in a CPG or client-data context.