Role Description
As a Learning Scientist, Early Numeracy, you will use your expertise in how young children learn mathematics to build models that represent the development of early math knowledge and skills. You will help identify what students learn, how their understanding grows over time, and how different concepts connect and build on one another. A key part of this role is developing ontologies and knowledge graphs that capture student learning progressions and serve as the foundation for product development. You will also design and conduct research studies to evaluate how effectively our products support teaching and learning for students in PreK-5 classrooms.
As an Individual Contributor, you will:
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Think creatively about applying learning science research within product constraints.
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Take a hands-on approach to solving problems.
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Communicate complex ideas and research findings clearly to both technical and non-technical audiences.
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Work closely with cross-functional teams to ensure learning science insights are translated into meaningful, evidence-based product experiences for students and educators.
Qualifications
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A PhD in developmental psychology, mathematics education, curriculum and instruction, cognitive psychology, or a related field with a mathematics education focus.
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Expertise in education trends in mathematics, such as grade bands (e.g., K-2, middle school) and areas of study (e.g., classroom technology use, personalized learning).
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Experience as an early-grades classroom teacher a plus.
Requirements
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Demonstrates a strong understanding of how students learn and develop mathematical knowledge, including key concepts such as the Standards for Mathematical Practice.
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Can clearly explain the progression of learning and the skills students need to be successful in math.
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Design and develop math learning progressions and knowledge maps that accurately represent how mathematical understanding and skills build over time.
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Distinguishes between educational policies, standards, and the specific skills students need to develop.
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Translates standards and learning expectations into clear, measurable student skills and competencies.
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Understands how changes in academic standards and educational requirements impact skill development and learning progression.
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Experience in applying either qualitative or quantitative methods to educational data.
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Familiarity interpreting student performance data.
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Proficiency with spreadsheet and productivity software and willingness to learn new tools.
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An AI-first approach to work.
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Understands business problems and delivers solutions for them.
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Communicates clearly and effectively.
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Works well with people across different teams.
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Takes initiative and can work independently.
Benefits
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Salary range: 95k β 105k.
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Application Deadline: The application window for this position is expected to close on August 10, 2026.