Manager, Innovation Project

Job Description

Summary:

Leads the design delivery and technical roadmap of digital learning solutions that improve skills development and business performance. This role defines product strategy designs scalable architectures evaluates and integrates emerging technologies (especially AI) and partners with L&D HR IT and business stakeholders to create measurable learning experiences and automation that drive adoption and outcomes.

Key responsibilities:

- Product strategy & roadmap

• Define the product vision strategy and multi-year roadmap for digital learning solutions (LXP LMS microlearning virtual labs coaching platforms assessment engines).

• Prioritize features based on business impact learner needs technical feasibility and analytics.

• Translate L&D objectives into measurable product outcomes (engagement completion competency improvement time-to-proficiency).

- User research & experience

• Collaborate with learning designers content teams and business SMEs to gather user needs map learner journeys and define learning scenarios.

• Define personas use cases acceptance criteria and UX requirements for learners managers admins and facilitators.

• Prototype concepts and run validation experiments (A/B tests pilot cohorts) to optimize experience and adoption.

- Technical architecture & integration

• Design and own the technical architecture for learning systems: LMS/LXP content repositories assessment engines single sign-on identity & access data pipelines and analytics layers.

• Define integration patterns and APIs for HRIS talent management CRM ERP and external content providers.

• Ensure secure data flows compliance with privacy laws (e.g. GDPR) and role-based authorization.

- AI & emerging technology adoption

• Identify evaluate and pilot AI capabilities to enhance learning: personalized recommendations adaptive learning paths AI tutoring/chat assistants automated content generation skill inference automated assessments and learning analytics.

• Partner with data scientists/ML engineers to define datasets model requirements evaluation metrics (fairness explainability accuracy) and deployment strategy.

• Maintain awareness of vendor offerings (LMS/LXP vendors AI platforms) and open-source options; recommend build vs buy decisions.

- Delivery & lifecycle management

• Lead agile product delivery (scrum or similar) with cross-functional teams: engineers ML/AI designers QA and L&D specialists.

• Define and track product backlogs release plans KPIs and feature adoption.

• Oversee content lifecycle and technical publishing workflows (SCORM xAPI / Experience API cmi5 LTI).

- Data analytics & measurement

• Define and implement learning analytics strategy: data model xAPI event taxonomy dashboards for managers and executives cohort analysis and ROI modeling.

• Use data to measure learning effectiveness skill progression and business impact; recommend iterative product improvements.

• Ensure instrumentation for A/B testing of features and personalized experiences.

- Governance security & compliance

• Establish governance for content data access model usage and third-party integrations.

• Implement security best practices (encryption least privilege) and vendor risk assessments.

• Ensure compliance with accessibility standards (WCAG) and internal policies.

- Stakeholder management & change

• Act as product owner to senior stakeholders HR/L&D leaders and business unit partners; communicate roadmap trade-offs and outcomes.

• Drive adoption through enablement plans manager toolkits onboarding flows and change management initiatives.

Required skills & experience

• Education: Bachelors in Computer Science Engineering Human-Computer Interaction Learning Sciences or related field. Masters preferred for senior roles.

• Experience: 6 years in product management or technical architecture roles; 3 years focused on learning technology HR tech or education technology preferred.

• Technical skills: system design API/integration architecture cloud platforms (AWS/Azure/GCP) data engineering fundamentals basic ML/AI understanding familiarity with xAPI/SCORM/LTI.

• AI/ML: hands-on experience evaluating or deploying AI solutions (NLP/chatbots recommendation systems content generation assessment scoring) and understanding of risks (bias hallucination).

• Tools: familiarity with LMS/LXP vendors analytics tools (Looker/Tableau/PowerBI) product management tools (Jira/Confluence) and data stacks.

• Communication: ability to translate technical trade-offs to non-technical stakeholders and build consensus.

Required Skills:

Preferred Skills:

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