Degreed - Director, Skills Intelligence & Learning Experiences

• Learning product leadership. You have shipped learning platforms or learning products that measurably helped people build skills, and you can point to the outcomes, not just the launches. You lead with both the learner and the enterprise buyer in mind, and you translate each into product decisions. • Learning product leadership. • Enterprise learning fluency. You understand how large organizations structure learning: academies, certifications, career paths, and cohort-based programs. You can translate those models into product decisions that hold up across very different customers. • Enterprise learning fluency. • Assessment design. You can define proficiency scales with clear, observable distinctions between levels, and explain those distinctions to customers when challenged. A background in psychometrics or learning assessment is a strong advantage. • Assessment design. • Taxonomy design depth. You have built classification systems that stay useful as domains evolve. You are familiar with frameworks such as O*NET and ESCO, and you understand how AI-based skill matching depends on taxonomy quality. • Taxonomy design depth. • Data product mindset. You have managed structured data with clear ownership, versioning, quality standards, and well-defined interfaces for downstream consumers. • Data product mindset. • Long-term systems thinking. You design systems that grow more accurate and useful as data accumulates, and you define the metrics that prove that improvement. • Long-term systems thinking. • ML fluency. You understand enough about how ML models consume training data to work effectively with engineers and to evaluate data quality, coverage, and sources of bias. • ML fluency. • Trust and fairness judgment. You are comfortable in ambiguous situations where standardized definitions and customer requirements do not fully align. You make consistent decisions and explain the reasoning behind them. • Trust and fairness judgment. • AI-assisted workflows. You use AI to accelerate taxonomy research, synthesize across sources, and prototype changes before implementation. • AI-assisted workflows. • Shape Degreed's learning experiences, from self-paced pathways to structured, cohort-based programs. • Own Degreed Academies, enabling enterprise customers to deliver certifications, onboarding, and other structured learning programs. • Decide how skill data powers personalized learning recommendations, including what content gets suggested to a learner next. • Direct the AI feature that identifies a learner's skill gaps and generates content to close them. • Design the full learner journey: how someone finds a skill gap, engages with content, and demonstrates they have closed it. • Own the full data model behind Degreed's skills product: how skills are defined, organized, and kept accurate as the system grows. • Run the platform enterprise clients use to adapt Degreed's skill list to their own internal language, combining AI suggestions with human review. • Design the rating scale used to measure skill proficiency, including the criteria that separate one level from the next. • Keep Degreed's skill data compatible with external frameworks and with enterprise HR systems. • Build the process by which every AI interaction across the product improves the underlying skill data over time, and measure that improvement with real numbers. • Evolve the skills model by making deliberate trade-offs between consistency, customer flexibility, and long-term product health. • Experience level: Expert (8+ years), including direct ownership of shipped learning products.