Head of Data – AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the creation of reusable data modeling strategies and a resilient technical framework.

• Develop shared libraries, models, and open-source tools for educational prototypes.

• Convert custom or lab-specific implementations into scalable solutions applicable across various products.

• Discover technical methods that mitigate risks associated with innovation and expedite the R&D process.

• Ensure that data science projects align with common objectives and maintain technical coherence within the AugmentED ecosystem.

• Collaborate with engineering to embed research-grade models into the foundational AugmentED platform.

• Guarantee that data modeling methodologies are modular and can be deployed within the platform’s infrastructure.

• Build and lead a high-performing team consisting of 3–6 data science consultants, including graduate students, postdoctoral researchers, and faculty members.

• Promote a culture of excellence, equity, and collaborative problem-solving.

• Encourage teamwork among AugmentED teams, university researchers, and educators.

⛳️ Requirements

• Extensive experience as a data scientist or a leader in applied AI/ML, focusing on designing and implementing data models, algorithms, and AI systems for tangible products.

• Eagerness to serve as both a hands-on contributor and a technical leader within a distributed network of researchers, engineers, and technical stakeholders.

• Profound knowledge of machine learning, AI, statistics, and contemporary data infrastructure.

• Proven experience in designing adaptable data architectures and technical bases for future scalability.

• Documented success in creating reusable data models, algorithms, and technical frameworks that extend beyond a single project or application.

• Experience collaborating with software engineering teams to transition AI and data science initiatives into production.

• Strong grasp of the complete AI development lifecycle, encompassing data pipelines, model creation, evaluation, deployment, and monitoring.

• Experience in establishing technical foundations that facilitate collaboration among research, engineering, and product teams.

• Experience defining requirements, articulating technical limitations, and aligning stakeholders with a unified technical vision.

• Background in educational research, learning science, or educational technology environments (preferred).

• Experience collaborating with academic researchers, universities, or interdisciplinary research teams (preferred).

• Commitment to educational equity and social impact.

• Strategic mindset balanced with practical technical skills.

• Proficient communicator capable of effectively collaborating with academic research partners.

• Strong growth mindset and comfort with ambiguity.

🏝️ Benefits

• Competitive salary compared to other nonprofit organizations.

• Comprehensive benefits package.

• Opportunities for personal and professional growth.

• Mission-driven and collaborative culture.

• Chance to influence the future of education.