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• Own external communications about the Coach product: launches, updates, partner communications, and content that helps prospective users and partners find us • Help build the messaging and positioning foundation for Coach: value propositions, ICP documents, comparative positioning, messaging frameworks • Audit existing product communications and propose how to evolve them into a reliable, proactive system • Collaborate with Product on launch planning, with Partner Success on partner and user communications, with Data on measurement and research input, and with Business Development on collateral & asset development • Partner with Product and Engineering on demo tools and product-adjacent assets that help the team bring Coach to life for partners and prospects • Define success metrics for launches and ongoing communications, track performance using our existing analytics stack (Google Analytics, Mailchimp, Hootsuite, Metabase), and use those signals to iterate on what's working

• Write code using modern web technologies with a special focus on accessibility and responsiveness • Collaborate with product designers, product managers, and backend engineers to shape design, experience, and functionality • Draft documentation outlining technical approaches to complex problems • Review code from team members • Write automated end-to-end tests to confirm functionality • Participate in design reviews of proposals for solutions to complex problems • Help investigate bug reports and engineering requests

• Design, build, and deploy predictive models that improve learner outcomes and product performance, including user behavior prediction, recommendations, ranking, and classification • Develop, own, and continuously improve end-to-end data science workflows, including ongoing model iteration, retraining, and performance monitoring over time • Take ownership of existing and new predictive models, diagnosing performance issues, adapting to data or product changes, and iterating to improve real-world impact over time • Partner closely with product, engineering, research, and leadership to translate ambiguous questions into data science solutions • Work closely with engineering partners to ship, maintain, and iterate on models in production; you will not be expected to build production infrastructure alone • Contribute to AI and model evaluation frameworks, including offline metrics, experimentation, and qualitative analysis • Analyze large, complex datasets to identify patterns, opportunities, and risks across our platforms • Communicate modeling approaches, assumptions, tradeoffs, and results clearly to technical and non-technical stakeholders • Write technical documentation, reports, and presentations that drive product and organizational decisions • Support responsible, ethical, and equitable use of data and AI in education-focused products

• Own top deals: Lead discovery, demo, negotiation, and contracting for high-value partnerships that anchor our GTM strategy. • Build and manage the pipeline: Oversee outreach, qualification, and forecasting. Maintain strong Salesforce discipline and ensure consistent visibility into performance metrics, with a focus on growing the number of active partner deployments and learners using Coach through those partners. • Spearhead the sales motion: Set weekly cadences, coach on discovery and objection handling, and model commercial excellence through hands-on selling. • Integrate AI and automation: Leverage AI to improve productivity, accelerate research, and test new approaches to prospecting and engagement. • Run rapid market experiments: testing segments, messaging, target profiles, and partnership models, then codify what works into clear, repeatable playbooks that reveal where the strongest traction exists. • Collaborate cross-functionally: Partner with Product, Engineering, and Impact teams to feed insights from the field back into the roadmap, messaging, and evidence-building. • Measure and optimize performance: Track conversion, cycle time, CAC, ROI, and scale metrics such as partners launched and active learners per deployment. Use data to guide resourcing and prioritize opportunities. • Drive GTM strategy: Help define market segmentation, ICPs, pricing logic, and value propositions across key buyer segments (job training, higher ed, corporate L&D). You’ll help decide where we bet next (by segment) and design experiments to prove or disprove those bets. • Guide/Develop assets: Partner with Impact and Marketing to create early case studies, ROI models, and success narratives that drive credibility and scale.