Leads end-to-end technology implementations across publishing companies, coordinating business, technology, vendor, and local publisher teams. Develops delivery, change, communications, training, readiness, rollout, adoption, and stabilization plans. Manages risks, dependencies, governance, stakeholder engagement, testing, pilots, hypercare, and transition to business-as-usual. Tracks adoption, user feedback, benefits, and continuous improvement while ensuring solutions are understood, adopted, and embedded in daily operations.

Leads Infinitas Learning’s group-wide data vision, governance, strategy, architecture, and operating model. Partners with executives, operating companies, product teams, and engineering to democratize data, build a data-driven culture, ensure responsible AI use, and deliver governed analytics and agentic data-analysis capabilities. Oversees data quality, privacy, security, architecture, tooling, prioritization, and the central data engineering backlog.

Product Data Scientist responsible for experimentation, causal inference, statistical modeling, learning-outcome evaluation, product metrics, data quality, and measurement standards. The role partners with Product, Design, Engineering, and senior stakeholders to generate trustworthy insights, evaluate AI-assisted analytical agents, improve instrumentation, and communicate evidence-based recommendations. Requires strong SQL, Python or R, applied statistics, product analytics, experimentation, and causal evaluation experience.