Job Title:

Learning Scientist, (Mathematics)

Location:

Remote (Can work from anywhere in United States) Who We Are NWEA is a division of Houghton Mifflin Harcourt that supports students and educators through research, assessment solutions, policy and advocacy services, professional learning and school improvement services that fight for equity, drive classroom impact and push for systemic change in our educational communities. For nearly 50 years, NWEA has developed innovative pre-K-12 assessments, including their flagship interim assessment, MAP Growth and their reading fluency and comprehension assessment, MAP Reading Fluency. For more information, visit NWEA.org to learn more. What You'll Do 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 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. You will work closely with cross-functional teams to ensure learning science insights are translated into meaningful, evidence-based product experiences for students and educators.

Responsibilities Deep Understanding of Mathematics Learning:

Demonstrates a strong understanding of how students learn and develop mathematical knowledge, including key concepts such as the Standards for Mathematical Practice. Can clearly explain the progression of learning and the skills students need to be successful in math.\nDesign and develop math learning progressions and knowledge maps that accurately represent how mathematical understanding and skills build over time, incorporating important concepts, relationships, and student learning pathways.

Policy and Educational Landscape Understanding:

Distinguishes between educational policies, standards, and the specific skills students need to develop.\nTranslates standards and learning expectations into clear, measurable student skills and competencies.\nUnderstands how changes in academic standards and educational requirements impact skill development and learning progression.\nApplies knowledge of evolving standards to ensure learning models and skill frameworks remain accurate and relevant.

Research and Analytical Skills:

Experience in applying either qualitative or quantitative methods to educational data.\nFamiliarity interpreting student performance data.\nProficiency with spreadsheet and productivity software and willingness to learn new tools.\nAn AI-first approach to work (willingness and commitment to implementing ethical use of AI to introduce efficiencies in work processes).

Collaboration andDelivery of Value:

Understandsbusiness problemsand delivers solutions forthem.\nCommunicates clearly and effectively. Raises concerns early and keeps leadership, partners, and stakeholders informed of important updates and challenges.\nWorks well with people across different teams. Is a reliable, trustworthy team member who contributes positively and follows through on commitments.\nTakes initiative and can work independently. Helps plan and manage their own work, prioritizes effectively, and delivers results based on their level of experience and responsibility. What You'll Need Education & Experience A PhD in developmental psychology, mathematics education, curriculum and instruction, cognitive psychology, or a related field with a mathematics education focus.\nExpertise 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).\nExperience as an early-grades classroom teacher a plus. Research & Analytical Skills A strong background in qualitative or quantitative research methods applied to learning sciences studies:\nQuantitative 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.\nQualitative 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.\nDetailed familiarity with mathematics content learning standards and learning models/trajectories across multiple grade bands.\nFamiliarity with interpreting student performance data.\nIn-depth understanding of learning models and trajectories in mathematics.\nProficiency 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 & Collaboration Stakeholder Engagement:

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.\n

Project Management:

Project management skills necessary to lead all learning-sciences aspect of a small-to-medium project, or a portion of a large and complex project.\n

Process:

Comfort following existing processes, including agile processes and tools.

Personal Attributes Drive:

Willing to dig into hands-on, individual-contributor work, including less glamorous stretches, with efficiency and a positive attitude.\n

Flexibility:

Comfortable pivoting as priorities shifts and moving between projects and grade bands as needed.\n

Bridge-building:

Curious about other teams and able to build connections across groups to see and serve the bigger picture.\n

Imagination:

Demonstrates imagination by looking for new ways of seeing, thinking, and working.\n

Inclusivity:

Listens, encourages, and respects differences; treats all people fairly, with honesty and transparency, and encourages open communication and feedback. Physical Requirement Might be in a stationary position for a considerable time (sitting and/or standing).\nConstantly operates computer.\nMust be able to collaborate with colleagues via conference calls and online meetings.

Salary range:

95k - 105k.

Application Deadline:

The application window for this position is expected to close on August 10, 2026. We encourage you to apply as soon as possible. The posting may be available past this date but is not guaranteed. HMH is fully committed to Equal Employment Opportunity and to attracting, retaining, developing and promoting the most qualified employees without regard to race, gender, color, religion, sexual orientation, family status, marital status, pregnancy, gender identity, ethnic/national origin, ancestry, age, disability, military status, genetic predisposition, citizenship status, status as a disabled veteran, recently separated veteran, Armed Forces service medal veteran, other covered veteran, or any other characteristic protected by federal, state or local law. We are dedicated to providing a work environment free from discrimination and harassment, and where employees are treated with respect and dignity. 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Learning Scientist (Mathematics)