I build practical AI and analytics systems that turn fragmented customer and operational signals into clearer decisions.
My work focuses on the layer between raw data and business action:
- Predictive customer experience and decision intelligence
- Voice-of-customer and conversation analytics
- Synthetic customer research and simulation
- Knowledge-grounded workforce enablement
- Deterministic AI orchestration and validation
- Operational friction and value-realization analysis
A forecasting and decision-support system spanning pre-period planning outlooks, in-period forecasts, operational pressure detection, recovery sensitivity, and model-learning controls.
Transforms synthetic feedback patterns into privacy-safe customer composites for policy and process hypothesis testing, then reuses those profiles in stateful service-training simulations.
Combines reusable AI personas with business-unit-specific knowledge, procedures, specialist roles, training behaviors, and escalation hierarchies.
Identifies where expected customer value breaks down across onboarding, digital activation, service handoffs, early product use, and expectation alignment.
Converts noisy service conversations into normalized speaker turns, privacy-safe evidence, operational classifications, customer-effort signals, and recommended actions.
Turns unstructured feedback into a governed taxonomy, classification-quality audit, friction scoreboard, and measurable 30/90-day action plan.
I separate probabilistic language generation from deterministic controls whenever the work requires reliability.
My projects commonly include:
- Explicit data and evidence boundaries
- Transparent confidence or priority logic
- Reproducible synthetic demonstrations
- Structured validation and failure handling
- Human-review checkpoints
- Executive-ready outputs
- Clear distinctions between evidence, inference, and scenario modeling
The public repositories on this profile use fictional organizations, synthetic datasets, independently created business rules, and clean-room implementations. They contain no employer, customer, or confidential information.
I am interested in senior and lead opportunities across:
- AI Product Management
- AI Enablement and Adoption
- Customer Success and CX Analytics
- Decision Intelligence
- Operational Analytics
- Applied AI Solutions