Head of Academics $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
You should want this role if you are the kind of academic leader who would rather build the system than comment on it. You are fluent enough in your subject to know what high-quality learning looks like, rigorous enough to turn that judgment into rubrics and AI-powered quality checks, and practical enough to act on messy data fast. You care about whether students actually improve, and you are comfortable being judged by that outcome.
2 Hour Learning is doing something the rest of the software and education world rarely attempts. There are no teachers, no textbooks, and no comfortable layer of traditional instruction underneath the product. AI is the operating model. In this role, you use it to generate and improve learning content, design interventions, monitor quality, and push the platform forward. The pace is closer to high-performance tech, consulting, or banking than conventional education, and the payoff is direct ownership over a subject’s student outcomes across campuses.
This role is about running a function. You will build AI-powered learning ecosystem enhancements, respond to student-performance signals with targeted interventions, create evidence-based decision records, and manage a team against clear standards tied to MAP, AP, SAT, and ISEE results. You will also work closely with product, engineering, and data science to define what the platform needs next. It is for someone who defaults to AI, self-serves on analysis, ships despite ambiguity, and owns results fully. It will frustrate anyone who prefers consensus-heavy pacing, light accountability, or the comfort of proven systems.
You will be a core leader inside the academics team, with real influence over how your subject performs and how the broader learning system improves. The team around you will rely on your standards, your judgment, and your ability to connect student data to action. If that sounds energizing rather than intimidating, you are likely the person this role is built for.
What you will be doing
- Learning Ecosystem Enhancements — AI-generated improvements to subject-specific K–12 learning experiences across content, adaptive pathways, and student interventions, informed by student feedback, analytics, assessments, and coaching insights.
- Data-Driven Academic Interventions — Targeted intervention plans for off-track students or cohorts, driven by MAP, AP, SAT, ISEE, and related performance data.
- Student Performance Decision Records — Repeatable, evidence-based decisions documenting student performance improvement actions, supported by dashboards, analytics, tickets, surveys, coaching calls, and assessment data.
- Learning Ecosystem Improvement Specs — Implementation-ready specifications for product, engineering, and data science enhancements, including problem statements, supporting evidence, expected student impact, and acceptance criteria.
What you will NOT be doing
- Repackaging traditional education in an AI wrapper. This isn't about replicating classroom instruction via screens – we're fundamentally reimagining learning from the ground up.
- Analyzing data in isolation. You'll be expected to regularly engage with K-12 students, valuing their feedback as essential input from our paying customers.
- Waiting for consensus to push boundaries. You'll champion a bold vision and rally others around data-driven results.
- Sticking to conventional methods. You'll be free to experiment with innovative approaches to motivation, assessment, and instruction.
- Fearing AI's impact on education. Here, you'll harness AI as an exciting tool to revolutionize learning, not as a threat to be mitigated.
Key responsibilities
Drive innovation in AI-powered, teacher-less education to deliver exceptional student outcomes across multiple campuses. Blend data analytics with regular student engagement to continuously optimize our learning ecosystem, as measured by AP exam performance and MAP assessment growth.
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
Applying for a role? Here’s what to expect.
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