Learning Scientist, Mathematics

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

📋 Description

• In the role of Learning Scientist specializing in Early Numeracy, you will leverage your knowledge of how young children acquire mathematical skills to create models that illustrate the progression of early math understanding and abilities.

• Assist in determining what students learn, the evolution of their comprehension over time, and the interconnections between various concepts.

• Create ontologies and knowledge graphs that reflect student learning pathways and serve as a basis for product development.

• Design and implement research studies to assess how effectively our products enhance teaching and learning for students in PreK-5 classrooms.

• Innovatively apply research in learning science within product limitations, adopt a hands-on approach to problem-solving, and convey complex ideas and research outcomes clearly to both technical and non-technical audiences.

• Collaborate closely with cross-functional teams to ensure that insights from learning science are transformed into impactful, evidence-based product experiences for both students and educators.

⛳️ Requirements

• A PhD in developmental psychology, mathematics education, curriculum and instruction, cognitive psychology, or a related field with a focus on mathematics education.

• Knowledge of educational trends in mathematics, including grade bands (e.g., K-2, middle school) and areas of study (e.g., classroom technology usage, personalized learning).

• Experience as a teacher in early grades is advantageous.

• A robust background in qualitative or quantitative research methods applied to studies in learning sciences: Quantitative track: Experience in applying and interpreting quantitative methods, including classical statistical methods, regression, and latent variable models (e.g., longitudinal, multilevel, or item response data), with proficiency in tools such as R or Python.

• Qualitative track: Experience in conducting, coding, and interpreting qualitative methods (e.g., cognitive interviews, grounded theory, design-based research), with proficiency in tools like ATLAS.ti, MAXQDA, or NVivo.

• Comprehensive understanding of mathematics content learning standards and learning models/trajectories across various grade levels.

• Familiarity with analyzing student performance data.

• Profound knowledge of learning models and trajectories in mathematics.

• Proficiency in spreadsheet and productivity software (e.g., Microsoft 365), along with a readiness to learn new tools and adopt an AI-first approach to your work.

🏝️ Benefits

• Health insurance

• Professional development opportunities

• Flexible work arrangements