Learning Scientist- Early Literacy

HMH

1d•$95,000 - $105,000•Remote

About The Position

The Learning Scientist, Early Literacy brings together deep expertise in how young children learn to read and develop as readers and writers with rigorous research methods to design and evaluate theoretically coherent products. The immediate focus of this role is early learning, where you will help build substantive models of how early literacy develops, capturing the skills and understandings students acquire and how they build on one another. These models are encoded as ontologies and knowledge graphs that underpin product development, and you will carry out studies to understand whether those products work for students and teachers in the early grades (PreK-5). While early literacy is the immediate focus, the role offers room to contribute more broadly as priorities evolve, whether across other areas and grade-bands of ELA such as comprehension and writing. As an Individual Contributor, the Learning Scientist will think flexibly and creatively about research applications within specific product constraints, roll up their sleeves for hands-on work, and clearly communicate ideas and findings to non-experts.

Requirements

A PhD or EdD in literacy/reading education, developmental psychology, cognitive psychology, curriculum and instruction, educational leadership, learning sciences, or a related field.
Deep expertise in early literacy, grounded in the science of reading, including foundational skills and how reading difficulties such as dyslexia emerge, paired with broad working knowledge across ELA such as comprehension and writing.
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 content learning standards and learning models/learning trajectories in early literacy.
Familiarity with interpreting student performance data.
Experience applying learning sciences to the design or revision of educational environments for diverse student populations.
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.
Communication skills (oral, written, and business) necessary to function effectively as a primary contact with internal project teams and to translate research findings for non-experts.
Project management skills necessary to lead all learning-science aspects of a small-to-medium project, or a portion of a large and complex project.
Comfort following existing processes, including agile processes and tools.
Willing to dig into hands-on, individual-contributor work, including less glamorous stretches, with efficiency and a positive attitude.
Comfortable pivoting as priorities shift and moving between projects and grade bands as needed.
Curious about other teams and able to build connections across groups to see and serve the bigger picture.
Demonstrates imagination by looking for new ways of seeing, thinking, and working.
Listens, encourages, and respects differences; treats all people fairly, with honesty and transparency, and encourages open communication and feedback.

Nice To Haves

Experience as an early-grades classroom teacher a plus.

Responsibilities

Apply educational research to develop and refine models of early student learning in early literacy, supporting the design, implementation, and validation of those models, including investigating early-grade learning attributes and their functional relationships.
Operationalize quantitative and/or qualitative research methods to design and execute studies that validate products and make explicit the cognitive models of early student learning.
Provide hands-on support that benefits from a learning-expert perspective, including learning-focused user research and data analysis to evaluate the effectiveness of specific product features and understand student learning outcomes.
Work closely with other learning scientists, engineers, UX researchers, product managers, and subject matter experts to develop and iteratively refine products that help early-grade teachers make instructionally relevant decisions.
Create clear, detailed documentation of your work, including white papers, internal memos, technical reports, and standard operating procedures.