CareerVillage.org

• 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