Learning Engineer - Instrumentation and Analysis – Learnvia - Simon Initiative

Learnvia is a new Carnegie Mellon University initiative focused on transforming post-secondary math education through research-driven, AI-enhanced courseware. As part of CMU’s broader efforts in learning science and educational technology, Learnvia collaborates closely with faculty, researchers, and institutional partners to develop innovative, evidence-based learning experiences.

We are seeking a Learning Engineer to help us deeply understand how learners interact with our platform and how their skills grow over time. You’ll ensure our platform is properly instrumented to capture meaningful learning data, then analyze that data to uncover insights that improve learner outcomes. This role sits at the intersection of learning science, learner data, and product — ideal for someone who wants to shape how modern learning platforms measure and accelerate learner success.

Core responsibilities include:

• Partner with engineering to design and implement event tracking across lessons, assessments, and practice activities.
• Ensure logging schemas capture fine-grained data such as attempts, hints, time-on-task, and error patterns.
• Audit and maintain data quality so insights are trustworthy and actionable.
• Analyze learner/learning data, identifying opportunities for improvement in content and feature design, coordinating efforts to implement the changes and track their impact on student learning.
• Apply learning science models (e.g., learning curves, item response theory, knowledge tracing) to track skill growth and predict mastery.
• Identify where learners struggle and what drives retention, progression, and engagement.
• Translate findings into recommendations for product, content, and instructional design improvements.
• Collaborate with product managers and designers to shape existing and new features based on learning data.
• Support A/B testing and experiments to measure the effectiveness of interventions.
• Deliver clear, business-oriented reports and dashboards for stakeholders.

Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

You should demonstrate:

• An ability to turn complex analyses into actionable insights for non-technical audiences.
• A passion for improving learner outcomes through data-driven and iterative content and feature design.
• Clear communication style for presenting complex topics clearly.

Qualifications:

• Bachelor’s degree required, Master’s degree preferred.
• At least three (3) years of experience in Learning Sciences, Data Science, Computer Science, or related field. Master’s degree preferred.
• Experience analyzing learner or user interaction data in large-scale learning platforms (higher ed learning platforms is a plus).
• Strong analytical and statistical skills (SQL, Python, R).
• Experience with cognitive modeling, learning curves, or educational data mining.
• Experience working with event logging, data pipelines, or instrumentation frameworks.
• Familiarity with mathematics instruction at the higher education level is a plus.
• Knowledge of learning science research, best practices in pedagogy and andragogy, and research-based principles of multimedia design is a plus.
• A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered.

Requirements:

• Successful pre-employment background check

Additional Information:

• Sponsorship: Applicants for this position must be currently legally authorized to work for CMU in the United States. CMU will not sponsor or take over the sponsorship of an employment visa for this opportunity.  Carnegie Mellon is not a qualifying employer for the STEM OPT benefit: only the 12-month OPT may be used to work at Carnegie Mellon.
• Fixed Term: This is a fixed-term position.
• A remote work option may be available for candidates with residency in Pennsylvania, California, New York, Virginia or Washington, D.C. All approved remote work arrangements are subject to an approved remote work agreement (RWA) as part of any offer of employment.

Joining the CMU team opens the door to an array of exceptional benefits.