Senior Director, Global Commercial Data, AI & Reporting Excellence

Senior Director, Global Commercial Data, AI & Reporting Excellence

The Senior Director sets the enterprise direction for how BBU commercial data, AI and reporting capabilities are designed, governed and scaled. The role owns the business strategy and value of key commercial data products and decision platforms, ensuring that trusted data and responsible AI improve decision quality, speed, productivity and commercial outcomes.

This is a senior business and technology savvy leadership role. The role translates commercial priorities into an AI-enabled data and digital roadmap; establishes clear product ownership, architecture principles, governance and reusable standards; and partners with Commercial IT, the Commercial Data Office, Finance, Enterprise AI teams, Operations, Insights, Analytics and Forecasting, global brand teams, regions and markets to deliver adoption and measurable value.

The portfolio includes pharmaceutical secondary market data and healthcare professional engagement data, together with the products, semantic definitions, interfaces, analytics and reporting platforms that make these assets usable. The role leads Data Product Owners and Platform Leads and is accountable for talent, delivery quality, investment choices, risk and value realisation.

• Set strategy and investment priorities: Define the multi-year vision and roadmap for commercial data, AI, reporting and digital decision platforms, aligned to BBU and GIBEx priorities.
• Own the business data architecture: Establish target-state principles for data domains, products, models, metadata, taxonomy, lineage, interoperability and access. Partner with Commercial IT on the technical architecture and prevent fragmented or duplicative solutions.
• Lead AI-enabled work redesign: Identify where predictive, generative and agentic AI can improve decisions and workflows; prioritise use cases by value, feasibility and risk; and move successful solutions from experiment to governed, scalable products.
• Ensure responsible AI: Embed human accountability, validation, explainability, privacy, security, bias controls, monitoring and auditability across the AI lifecycle, in line with applicable policies and regulation.
• Lead the data-product portfolio: Own product vision, outcomes, lifecycle, roadmaps and backlogs for commercial data products and platforms. Apply user discovery and product management to anticipate and solve priority business problems rather than produce outputs on request.
• Create trusted data: Establish clear ownership, quality standards, critical data definitions, controls and issue-resolution routes for pharmaceutical secondary data and HCP engagement data.
• Modernise reporting and decision support: Simplify and standardise enterprise KPIs, reporting and executive performance views; increase reuse and self-service; and retire low-value or duplicative products.
• Deliver measurable value: Define and track adoption, decision impact, productivity, quality, risk and return on investment. Use evidence to stop, redesign or scale work.
• Orchestrate enterprise delivery: Align GIBEx, global brands, regions, markets, Commercial IT, the Commercial Data Office, Finance, AI teams and Operations around shared priorities, decision rights, standards and delivery plans.
• Lead talent and partners: Build a high-performing, globally distributed team; develop AI, product, data and commercial capability; manage vendors, budgets, capacity and delivery risk; and create clear accountability across direct and matrix teams.
• Advise senior leaders: Translate complex data and technology choices into clear business options, trade-offs, recommendations and risks for executive decisions.
• Leaders use one trusted, decision-ready view of commercial performance.
• Priority data and AI products have clear owners, standards, controls, adoption measures and realised business value.
• AI-enabled workflows are scaled responsibly beyond pilots, with defined human accountability and evidence of improved quality, speed or productivity.
• Data duplication and manual reporting reduce as reusable products, common definitions and governed self-service increase.
• The team has stronger AI, data architecture, digital product and commercial decision skills, with a sustainable succession pipeline.

Scope: Global | Commercial data, AI, digital platforms and performance reporting | Approximately five direct reports plus matrix delivery teams