Senior Director, Global Commercial Data, AI & Reporting Excellence

AstraZeneca; España; Presencial; EUR 180.000 - 240.000; Jornada completa

Descripción de la vacante

AstraZeneca is seeking a Senior Director, Global Commercial Data, AI & Reporting Excellence to set the enterprise direction for data, AI and reporting platforms across the organization and to own the business strategy and value of key data products.

You will partner with Commercial IT, Finance, Enterprise AI teams and global brands to drive adoption, governance, and measurable value while leading a distributed team to deliver scalable, trusted data and decision-support capabilities.

Formación

• Significant senior leadership experience in commercial data, analytics, AI or data platforms in pharma or regulated sectors.
• Proven ownership of an enterprise data/AI strategy with product lifecycle experience.
• Strong knowledge of modern data architecture, cloud platforms and APIs.

Responsabilidades

• Set strategy and investment priorities for commercial data, AI and reporting platforms.
• Own data architecture, target-state principles and interoperability across data domains.
• Lead AI-enabled work redesign and prioritize use cases by value and risk.
• Ensure responsible AI with privacy, security and governance controls.
• Lead the data-product portfolio including vision, roadmaps and backlogs.
• Create trusted data with clear ownership and quality standards.
• Modernise reporting and decision support for standardized KPIs and self-service.
• Deliver measurable value through adoption, impact and ROI tracking.
• Orchestrate enterprise delivery across GIBEx, brands, regions and functions.
• Lead talent and partners, manage budgets and delivery risk.
• Advise senior leaders with clear business options and risks.

Conocimientos

Senior leadership

Data strategy

Data architecture

AI literacy

Product management

Cross-functional leadership

Regulatory aware

Descripción del empleo

Senior Director, Global Commercial Data, AI & Reporting Excellence

Reports to: VP, Global Insights & Business Excellence (GIBEx), BBU

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

Role purpose

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.

Key responsibilities

• 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.

Essential experience and skills

• Significant senior leadership experience in commercial data, analytics, AI, digital products or data platforms within pharmaceuticals, life sciences or another complex, regulated sector.
• Demonstrated ownership of an enterprise data and AI strategy, with evidence of moving products from concept through deployment, adoption, operation and measurable value.
• Strong working knowledge of modern data architecture, including domain-based data products, cloud data platforms, integration patterns and APIs, semantic layers, master and reference data, metadata, lineage, identity and access, and structured and unstructured data.
• Strong AI literacy across machine learning, generative AI and agentic workflows, including model and use-case evaluation, human-in-the-loop design, retrieval approaches, monitoring and responsible AI controls. The role does not require hands-on model coding but does require credible technical judgement.
• Expertise in data-product and platform management: customer discovery, product vision, roadmaps, prioritis