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At Learning Commons, we operate at the intersection of technology, research, and philanthropy. We pair product development with grantmaking to scale proven teaching and learning practices for the benefit of every learner. We aim to bring learning science into the tools educators and students use every day.
Our work is grounded in a deep belief: when technology reflects the realities of classrooms and the science of how students learn, it can meaningfully strengthen teaching and unlock new possibilities for students. The rise of generative AI offers us a once-in-a-generation opportunity to dramatically accelerate the translation of research insights into practical, classroom-ready tools; tools that honor teachers’ expertise, adapt to students’ needs, and make effective learning practices easier to access, implement, and sustain.
In today’s fragmented edtech landscape, school districts are often left piecing together products that don’t always align with curricula or instructional needs. While AI holds enormous potential to support teachers and students, it can only deliver on that promise when grounded in research, high-quality educational data, and expert evaluation. That’s why we’re building open, public-purpose infrastructure — datasets, rubrics, and resources — that help raise the standard for educational tools and create more consistent, impactful learning experiences for all students and teachers.
We are seeking an Applied Learning Scientist to support our team in translating learning science research into educational products and partnerships. This position offers the opportunity to contribute to initiatives that inform our product development strategy and support pedagogical innovation. You'll work on diverse projects and assignments while building your expertise in applied learning science within the educational technology space.
The Redwood City, CA base pay range for this role is $153,000 - $210,100. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
6 months ago
153,000 – 210,100 USD
per year
Grade
Lead
Work Format
Hybrid
Employment
Full-time
English Level
C1 - Advanced
Relocation
Bay Area
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