AI-Driven Science Learning Strategist

$100,000 USD/year ^{Pay is set based on global value, not the local market. Most roles = hourly rate x 40 hrs x 50 weeks} ($50 USD/hour)

• Decoding complex patterns in student learning data using AI, transforming these insights into groundbreaking strategies that revolutionize how science is taught and learned.
• Engineering AI-powered virtual experiments and simulations, bringing abstract scientific concepts to life in ways that captivate and educate students.
• Designing adaptive learning pathways that evolve in real-time, making intricate scientific theories accessible and engaging for students across all proficiency levels.
• Collaborating with a diverse team of educators, scientists, and AI experts to push the boundaries of science education, directly impacting the learning journey of thousands of students.
• Translating dense scientific literature into digestible, AI-enhanced content that not only educates students but ignites their passion for scientific inquiry.

• Managing traditional science curriculums or handling administrative tasks—this role is about innovation and strategic improvement in how science is taught and learned.
• Working in a silo—you'll be part of a dynamic team pushing the frontiers of AI in science education.
• Focusing solely on theory—every AI model you develop will directly impact how students understand and apply scientific principles in the real world.

Drive measurable improvements in student science learning outcomes through AI-driven analysis and implementation, as demonstrated by a 2x acceleration in concept mastery across various scientific domains (biology, chemistry, physics, etc.) and grade levels.

• Bachelor's degree or higher in a scientific field (such as Biology, Physics, Chemistry, or similar)
• 3+ years of experience teaching science or developing science curriculum, with demonstrable impact on learning outcomes
• Basic coding abilities in any programming language
• Experience designing, implementing, or using AI systems for tasks such as content generation, data analysis, or adaptive learning
• Demonstrated ability to analyze complex data and derive actionable insights from it
• Excellent communication skills, with the ability to explain complex scientific concepts to diverse stakeholders in a professional setting