Vice President Learning $200,000 USD/year Pay is set based on global value, not the local market.
Most roles = hourly rate x 40 hrs x 50 weeks
Description
This position is designed for an academic leader who prefers to construct educational systems rather than critique them from the sidelines. You possess sufficient subject-matter expertise to recognize high-caliber learning when you see it, the discipline to translate that understanding into measurable rubrics and AI-driven quality controls, and the pragmatism to make decisions quickly using imperfect information. Student improvement is your primary concern, and you accept accountability for that metric.
2 Hour Learning pursues an objective that most software and education companies seldom undertake. The model operates without teachers, textbooks, or the safety net of traditional pedagogy. AI serves as the foundational operating system. In this capacity, you will deploy it to produce and refine learning materials, architect interventions, oversee quality assurance, and advance the platform. The working tempo resembles high-stakes technology, strategy consulting, or investment banking more than conventional academia, and the reward is direct control over subject-level student performance across multiple locations.
This is a functional leadership position. You will develop AI-enabled enhancements to the learning environment, execute interventions informed by student performance indicators, document evidence-backed decisions, and lead a team measured by outcomes on MAP, AP, SAT, and ISEE assessments. You will also collaborate closely with product, engineering, and data science teams to articulate platform requirements. The role suits someone who instinctively turns to AI, conducts independent analysis, delivers work amid uncertainty, and accepts full ownership of results. It will frustrate those who favor consensus-driven workflows, minimal accountability, or reliance on established methodologies.
You will serve as a senior leader within the academics division, holding substantial influence over your subject's performance and the evolution of the learning system as a whole. Your colleagues will depend on your standards, discernment, and capacity to translate student data into actionable decisions. If that prospect feels motivating rather than daunting, you are probably well-suited for this position.
What you will be doing
- Learning Ecosystem Enhancements — AI-driven refinements to subject-specific K–12 learning experiences spanning content, adaptive pathways, and student interventions, shaped by student feedback, analytics, assessment results, and coaching observations.
- Data-Driven Academic Interventions — Focused intervention strategies for underperforming students or groups, guided by MAP, AP, SAT, ISEE, and comparable performance metrics.
- Student Performance Decision Records — Systematic, evidence-supported documentation of actions taken to improve student outcomes, backed by dashboards, analytics, support tickets, surveys, coaching interactions, and assessment data.
- Learning Ecosystem Improvement Specs — Deployment-ready specifications for product, engineering, and data science teams, encompassing problem definitions, supporting evidence, anticipated student impact, and acceptance criteria.
What you will NOT be doing
- Wrapping traditional education in an AI veneer. This is not about digitizing classroom instruction – we are reconstructing learning from first principles.
- Conducting data analysis in a vacuum. You will engage directly and regularly with K-12 students, treating their input as critical feedback from paying customers.
- Seeking unanimous approval before taking bold action. You will advance an ambitious vision and mobilize others through evidence-based outcomes.
- Adhering to conventional practices. You will have latitude to test novel strategies for motivation, assessment, and instruction.
- Treating AI as a threat to education. In this environment, you will leverage AI as a transformative instrument for reimagining learning.
Key responsibilities
Lead the advancement of AI-powered, teacher-less education to achieve outstanding student results across numerous campuses. Integrate data analysis with consistent student interaction to continually refine our learning ecosystem, with success measured by AP exam scores and MAP assessment gains.
Candidate requirements
- Master's degree or higher in Educational Science, Learning Science, Psychology, Psychometrics, Instructional Design, or a related field
- At least 5 years of experience in academic or EdTech leadership roles, with direct people management responsibility (hiring, performance evaluation, coaching, termination decisions)
- Demonstrated experience using AI tools as part of day-to-day professional workflows, and willingness to rely on AI extensively to improve academic and operational outcomes.
- Strong understanding of learning science principles, such as Cognitive Load Theory and Mayer's Multimedia Principles, and data-driven educational approaches
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