Learning Innovation Specialist

Description

SUMMARY

The Learning Innovation Specialist plays a pivotal role in designing, developing, and implementing innovative, technology-driven learning solutions that enhance learner engagement, improve knowledge retention, and drive workforce development. This role will work closely with Education Portfolio Managers, Education Operations Sr. Manager, Learning Systems Specialist, and Education Product Development Manager to identify trends, experiment with emerging technologies, and integrate immersive, blended, and personalized learning experiences aligned with our strategic objectives. This position requires a blend of Learning Engineering expertise, Technology Commercialization experience, as well as Data Science, and AI knowledge. The successful candidate will work cross-functionally to align these innovations with organizational goals and market demands, advancing our mission through cutting-edge learning technologies.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties may be assigned.

• Drive the end-to-end product innovation process for learning solutions, including ideation, market validation, design, and implementation.
• Develop and test prototypes of learning products, leveraging emerging technologies like VR, AR, AI, ensuring alignment with market needs and learner preferences.
• Adopt a UX-focused listening strategy to identify high-impact use cases for innovative learning interventions, ensuring alignment with organizational and market needs.
• In partnership with Education Portfolio Managers, analyze competitors, evaluate potential technologies, and conduct user testing to validate product concepts and uncover opportunities for differentiation and value creation.
• Develop storyboards, prototypes, and proof-of-concept designs to test new ideas and solicit feedback from key stakeholders.
• Employ agile product development principles to test, iterate, and scale learning solutions, using data and feedback to refine adaptive models and improve competency alignment over time.
• Collaborate with content experts to define and refine product features, ensuring learning products meet educational standards and business objectives.
• Stay abreast of emerging trends in Learning Engineering, Adaptive Learning Systems, and Learning Analytics, translating insights into actionable ideas that add value to the learning experience.
• Conduct research on new learning technologies and innovative methods for training delivery, sharing findings, and best practices with the broader team.
• Use metrics and analytics to measure product effectiveness, assess market adoption, and implement iterative improvements based on feedback and performance data.
• Work closely with marketing and sales teams to develop go-to-market strategies, positioning, and promotional plans that maximize product impact and reach.
• Collaborate with external partners and industry experts to pilot and scale solutions, driving adoption of new methods and technology within the organization.

Qualifications

TRAVEL REQUIREMENTS

Some domestic and/or occasional international travel (up to 25%) may be required to support instructor and partner onboarding, training, and relationship management efforts. Passport is required.

EDUCATION and/or EXPERIENCE

• Bachelor’s degree in Software Engineering, Data Science, Instructional Design, or a related field is required. Master’s degree preferred.
• 5+ years of experience with adaptive learning technologies, data analytics, and/or the use of AI to personalize learning environments; familiarity with competency-based education models is highly desirable.
• Proficiency with machine learning, data analytics, and adaptive learning technologies.
• Proven experience in agile technology product development practices and principles.
• Experience scaling immersive/extended reality learning solutions in a heavy industrial and/or military environment is preferred. Familiarity with the Department of Defense Total Learning Architecture is a plus.
• Experience with data visualization (e.g., Tableau, Power BI) and programming languages for data science (e.g., Python, R)