Leadership + Executive Statement
A Robust, Capable Player/Coach for Your New AI Team
Executive Consideration
Leadership Experience
- Proven Track Record in End-to-End AI/ML Lifecycle: Successfully led and delivered complex data science and AI engineering projects from ideation and research to deployment and MLOps, demonstrating expertise across the entire development pipeline.
- Strategic Vision & Impact: Consistently translated business objectives into actionable data science strategies, driving significant improvements in key metrics, revenue generation, and operational efficiency through innovative AI solutions.
- Technical Acumen & Innovation: Maintained a deep hands-on understanding of cutting-edge AI/ML technologies, fostering an environment of continuous learning and leveraging emerging techniques to solve challenging problems and push technical boundaries.
- Cross-Functional Collaboration & Communication: Mastered the art of bridging the gap between highly technical teams and non-technical stakeholders, effectively communicating complex ideas, building consensus, and driving successful outcomes through strong interpersonal skills.
- Mentorship & Team Development: Cultivated high-performing data science and AI engineering teams by actively mentoring junior and senior engineers, fostering a culture of ownership, knowledge sharing, and professional growth.
- Architectural Leadership & Scalability: Designed and implemented robust, scalable, and high-performance AI architectures, ensuring the reliability, efficiency, and future-proofing of critical data and AI systems within enterprise environments.
Why Have I Been a Successful Leader
- Strategic Vision: My ability to see beyond the immediate technical implementation and articulate a clear, long-term vision for how AI will transform the company's products, services, and operations to achieve a competitive advantage.
- Deep Practical Acumen: In addition to hands-on coding daily, I possess a strong foundational understanding of AI/ML concepts, architectures, and the practical challenges of building and deploying AI systems. This allows for informed decision-making and credible leadership.
- Adaptability and Agility: The AI landscape is rapidly evolving. I embrace constant change, fostering a culture of experimentation, and a willingness to pivot strategies quickly based on new insights and technological advancements.
- Ethical Leadership & Responsible AI: Recognizing and proactively addressing the ethical implications of AI - including bias, fairness, transparency, and data privacy - is paramount. My leadership ensures AI is developed and used responsibly and for the benefit of all stakeholders.
- Exceptional Communication & Storytelling: My ability to translate complex AI concepts into clear, compelling narratives for both technical and non-technical audiences has been crucial. This includes articulating the "why" behind AI initiatives and their business impact.
- Talent Development & Empowerment: Beyond just hiring, I invest in the growth of my teams, fostering a culture of continuous learning, mentorship, and psychological safety that empowers engineers to innovate and take ownership.
- Cross-Functional Collaboration: AI initiatives rarely exist in a vacuum. I am skilled at building strong relationships and fostering collaboration across engineering, product, business development, and even legal teams to ensure successful integration and adoption.
- Problem-Solving & Critical Thinking: AI often deals with ambiguous and ill-defined problems. I possess the critical thinking skills to break down complex challenges, identify key assumptions, and guide my teams toward innovative solutions.
- Business Acumen & ROI Focus: Understanding core business objectives and how AI can directly contribute to revenue, cost savings, or customer satisfaction is vital. I am successful at connecting AI initiatives back to measurable business outcomes.
- Curiosity & Continuous Learning: The best AI leaders are inherently curious and committed to staying abreast of the latest research, tools, and best practices in the field. I encourage this same curiosity within my teams, fostering a learning-oriented environment.
Bleeding Edge AI Scientist & Engineer
I Can Help Your Company...
- Accelerate AI Product Development & Time-to-Market: Leverage my experience in leading end-to-end AI/ML lifecycles to streamline the development process, optimize resource allocation, and rapidly bring innovative AI products and features to market.
- Establish a Robust & Scalable AI Infrastructure: Design, implement, and optimize a cutting-edge, enterprise-grade AI infrastructure, ensuring the stability, efficiency, and scalability required to support current and future AI initiatives.
- Drive Strategic AI Innovation & Competitive Advantage: Translate business challenges into strategic AI opportunities, identifying and championing the development of AI solutions that differentiate the company, create new revenue streams, and enhance competitive positioning.
- Elevate Technical Excellence & Best Practices: Instill a culture of engineering excellence within the AI teams by implementing industry best practices in model development, MLOps, data governance, and ethical AI, leading to higher quality and more reliable AI offerings.
- Attract, Develop, and Retain Top AI Talent: Utilize my strong leadership and mentorship skills to build a world-class AI organization, attracting top-tier talent, fostering their growth, and creating an environment where they can thrive and contribute maximally.
- Ensure Measurable ROI and Business Impact from AI: Implement rigorous metrics and evaluation frameworks to demonstrate the tangible business value of AI investments, ensuring that AI initiatives are directly contributing to your company's strategic goals and bottom line.
Education & Continuing Education
Chief AI Officer Program, Miami Herbert Business School
University of Miami | Miami, Florida
This 8-month certificate program is designed for experienced executives and managers to master AI-driven solutions, enabling exploration, implementation, and alignment of AI to business objectives for growth and competitiveness. Applied for entry: Fall 2026
Graduate School, Research Methodology and Quantitative Methods
University of Nebraska at Omaha | 2003 - 2008
Graduate project: Omaha MAACLink: HMIS & Social Services Software — As part of my academic work, I was involved in the initial concept and program architecture for the Omaha, Neb. MAACLink Homeless Management Information System (HMIS). This role required me to translate the complex needs of social service providers into a foundational, technical blueprint. The experience provided hands-on practice in systems design and understanding the foundational elements of large-scale software development.
Graduate focus: Quantitative Analysis & Diffusion Theory —My studies focused on quantitative research methodologies, including surveys and computational analysis, to understand how new ideas and technologies spread. I placed a particular emphasis on diffusion theory, which provides a framework for understanding how users adopt innovations. This involved analyzing the factors that distinguish early adopters (innovators and visionaries) from late adopters (skeptics and laggards). By combining software design with a deep understanding of user behavior, I gained a unique perspective on the entire lifecycle of a technological solution—from its initial concept to its adoption by the end-user.
Bachelor of Science (B.S.), Communication and Media Studies
University of Wisconsin-Superior | 1997 - 2001
Activities and societies: University newspaper; university housing residential assistant (R.A.) Extensive studies in speech communication, group communication, non-verbal communication studies, negotiation/arbitration studies, conflict resolution. Extensive study in negotiation from the published work of William Ury and the Harvard Negotiation Project (HNP).