Create and maintain procedures for identifying areas of risks and opportunities in your organizations quality performance through identification of emerging trends with supporting analysis (Identify/develop key metrics for performance management).

More Uses of the Learning Analytics Toolkit:

  • Manage work with organizational leadership at all levels to develop solutions that directly align with your organizations strategic plan and unlock new business opportunities.
  • Devise: partners with department on the implementation of designs for a variety of modalities, platforms, and scales often leveraging emerging educational technologies, learning science research, and learning analytics.
  • Identify, develop, and maintain relationships with prospective external partners to adopt content aligned with their organizations learning and development goals.
  • Apply project management, communication, relationship management, design, quality assurance, and consultative skills to collaborate with department, course teams, administrators, vendors and other stakeholders.
  • Foster a culture of operational excellence to drive higher levels of system reliability, feature quality and resiliency through modern delivery practices that eliminate operational risks and impacts to service levels.
  • Evaluate: own the strategy and execution as the subject matter expert of end to end quality data as it ties to the quality management system working closely with quality engineers and quality assurance teams.
  • Develop protocol and program data interfaces across information platforms that are used for analytics and Business/ Process Intelligence as part of a digital ecosystem.
  • Provide engineering and technical leadership for project planning and implementation activities with internal and external teams as it relates to analytics, platform integration, digital ecosystem, AI and Machine Learning.
  • Audit: leverage statistical, econometric, stochastic, operations research, predictive modeling, simulation, optimization (linear, mixed integer, constraint programming), and/or machine learning analytics techniques.
  • Ensure your organization prioritizes customer requests based on technology product vision, strategy, end user value and schedules appropriately as a project or task consistent with established standards and/or guidelines.
  • Develop strategies to create and maintain insightful automated dashboards and data visualization to track core metrics and extract useful insights for your organization.
  • Ensure you lead design of dashboards and reports for self and others to provide insights to the business, ensuring execution and delivery of weekly, monthly and quarterly management quality reporting.
  • Contribute to technology innovation and research, technology transfer from research to development, algorithm development, simulation, and modeling.
  • Ensure you lead projects as the analytics and data science subject matter expert in support of end to end quality data and analytics working closely with Quality Engineers and Quality Assurance teams.
  • Steer: work across business areas to influence and support the creation of a data feedback loop as part of the product development life cycle in support of data driven decision making.


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