Michael Stefanini
Chief Data Officer & Director of Artificial Intelligence Tutor Perini
With over 30 years of NASA and industry experience in computer engineering, information technologies, and product lifecycle management, Mike brings senior leadership and technical experience to bear across IT, business, and engineering disciplines. He has proven experience in:
- Creating and leading large corporate organizations
- Launching Small Business and Consulting Startups
- Understanding, designing, and optimizing spacecraft engineering processes
- Monitoring and predicting trends using data science & analytics
- Maximizing value with process and technology transformations
- Optimizing Portfolios and aligning them with corporate goals, reducing waste, and focusing value
- Managing and delivering large-scale projects and services
- Creating and training effective Program & Project Management Offices (PMOs)
- Ensuring value with proven project metrics, frameworks, and governance policies
- Maintaining executive visibility & communications with custom executive dashboards
- Designing and operating IT services and delivering service-oriented solutions
- Working with executives to develop goal-oriented enterprise policy and processes
Michael is passionate about driving digital transformation and creating business value. He has a proven track record of delivering mission-critical solutions, process improvements, and strategic advancements in various domains. He is a certified Project Management Professional (PMP), Master Project Manager (MPM), Agile Project Manager, and Scrum Master. He is also certified in ITIL, Lean/6-Sigma, and other areas. He has received multiple honors and awards from NASA and JPL, including the NASA Medal for Achievement, for his exceptional accomplishments and leadership.
Seminars
- Creating formalized, role-based governance policies around meeting foundational CDAO criteria for control and compliance
- Sharing our DART (Data, AI, and Reporting Technologies) Principles that explicitly define responsible AI use, bias detection, and explainability expectations
- Discussing our Technology Evaluation & Innovation Policy that institutionalizes a tiered PoC–Prototype–Pilot process, which balances innovation with risk management
- Outlining how DART embeds change management, data literacy, and role-based access. This ensures we forge a data-driven culture based on trust, responsibility, and adaptability
