Learning Scientist, Mathematics

🕒 3 days ago

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HMH

1001 - 5000 employees

📚 Education

🛍️ eCommerce

Education • eCommerce • Professional Development

HMH is an educational company that specializes in providing comprehensive curriculum and assessment solutions across a wide spectrum of subjects. They offer programs and resources for literacy, mathematics, science, social studies, and social-emotional learning for K-12 students. Additionally, HMH focuses on professional development for educators to enhance instructional strategies and improve student outcomes.

📋 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. • Help identify what students learn, how their understanding grows over time, and how different concepts connect and build on one another. • Develop ontologies and knowledge graphs that capture student learning progressions and serve as the foundation for product development. • Design and conduct research studies to evaluate how effectively our products support teaching and learning for students in PreK-5 classrooms. • Think creatively about applying learning science research within product constraints, take a hands-on approach to solving problems, and communicate complex ideas and research findings clearly to both technical and non-technical audiences. • Work closely with cross-functional teams to ensure learning science insights are translated into meaningful, evidence-based product experiences for students and educators.

🎯 Requirements

• A PhD in developmental psychology, mathematics education, curriculum and instruction, cognitive psychology, or a related field with a mathematics education focus. • 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). • Experience as an early-grades classroom teacher a plus. • A strong background in qualitative or quantitative research methods applied to learning sciences studies: Quantitative track: Experience 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 conducting, coding, and interpreting qualitative methods (e.g., cognitive interviews, grounded theory, design-based research), with proficiency in tools such as ATLAS.ti, MAXQDA, or NVivo. • Detailed familiarity with mathematics content learning standards and learning models/trajectories across multiple grade bands. • Familiarity with interpreting student performance data. • In-depth understanding of learning models and trajectories in mathematics. • Proficiency with spreadsheet and productivity software (e.g., Microsoft 365), and a willingness to learn new tools and take an AI-first approach to the work.

🏖️ Benefits

• Health insurance • Professional development opportunities • Flexible work arrangements

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