Experience
From enterprise engineering into data products, B2B SaaS and AI platform leadership. Employers and client environments are shown separately.
Work across retail analytics and data-product needs in a large-enterprise client environment, with emphasis on reporting, reusable metrics and platform consumption rather than internal architecture disclosure.
Management reporting requirements · Downstream data consumers · Reusable business metrics · Semantic models · Scope and dependencies · Acceptance criteria
Related case: Retail Analytics Data Product
Architecture and product work for executive decision-intelligence capabilities, translating ambiguous governance and workflow needs into prioritised AI product capabilities in a high-security environment.
Executive workflows · Ambiguous requirements · Capability prioritisation · Summarisation · Decision tracking · Risk signals
Related case: Executive Decision Intelligence
Client work across AI hiring, developer copilot and related B2B SaaS workflows, spanning product requirements, workflow design, analytics and delivery.
−40% support effort and −45% release cycle are 2025 period-level delivery metrics, not a single-client P&L.
Product requirements · Workflow design · Developer copilot · Recruitment technology · Product analytics · Usage-based monetisation
Related cases: AI Hiring SaaS · AI Developer Copilot
Roadmap and platform work for a logistics SaaS product: forecasting, analytics, operational workflows and platform economics.
Roadmap translation · Logistics SaaS · Forecasting · Analytics platform · Operational workflows · Product analytics
Related case: Logistics Data Platform
Enterprise GIS and geospatial analytics platform work, including cloud/ML delivery for operational decision support.
Enterprise GIS requirements · Geospatial analytics · Platform capabilities · Cloud / ML delivery · Operational decision support
Related case: GIS / Analytics Platform
Enterprise Engineering & Technology Consulting Foundation
Foundation years close to the technology: enterprise software, data and AI capabilities across consulting and engineering environments, including product-owner collaboration and client stakeholder work.
Enterprise software · APIs · Cloud · Data pipelines · Analytics · Distributed systems