D&AI DELIVERY MANAGER

We’re building the future of medical dermatology by focusing on unmet patient needs and giving people the space to think independently, take ownership and make an impact that matters.

Our purpose is simple: to transform patients’ lives by addressing real needs. We work with care, act with courage, keep things simple and focus our innovation where it makes a difference.

Recognised as a Top Employer in Spain since 2008 and in Germany since 2025, we continue to invest in an environment where people can grow and move forward.

If you care differently, you belong here.

Mission

The Data & AI Delivery Manager is responsible for leading the delivery and continuous evolution of Data, Analytics, AI and Generative AI products and services, ensuring they generate measurable business value.

Acting as a bridge between Business and IT, this role drives execution, adoption and value realization across the Data & AI portfolio. Working with a high degree of autonomy, the Delivery Manager coordinates internal teams, external partners and key stakeholders to ensure successful outcomes and continuous improvement.

• Lead the end-to-end delivery of Data, Analytics, AI and Generative AI initiatives aligned with business priorities.
• Manage Data & AI products and services throughout their lifecycle, balancing value, budget, resources and delivery commitments.
• Partner with business stakeholders, Product Owners and Sponsors to shape demand, challenge requirements and prioritize initiatives.
• Drive product adoption, value realization and continuous improvement based on business feedback and usage insights.
• Promote agile delivery practices and outcome-driven ways of working.
• Define and track success metrics, KPIs and OKRs aligned with business objectives.
• Ensure effective governance, planning, risk management and stakeholder alignment.
• Manage external suppliers and technology partners, ensuring delivery quality and performance.

• 10+ years of experience in IT, Digital, Data & Analytics or AI-related delivery roles.
• Proven experience leading complex initiatives in agile and cross-functional environments.
• Experience delivering Data, Analytics, AI and/or Generative AI solutions in enterprise settings.
• Strong stakeholder management, influencing and relationship-building skills.
• Experience driving adoption, change management and business value realization.
• Experience managing demand pipelines, product roadmaps and prioritization processes.
• Experience collaborating with business leaders, Product Owners, Architecture, Security, Legal and external providers.
• Experience managing vendors and service partners.
• Fluent in English.

Technical & AI Knowledge

• Good understanding of modern Data & AI platforms, architectures and delivery models.
• Experience with technologies such as Azure, Databricks, Power BI and Power Platform.
• Familiarity with Generative AI solutions and enterprise AI platforms such as Microsoft Copilot, Copilot Studio, Claude or similar technologies.
• Understanding of AI delivery patterns including AI Assistants, AI Agents and Retrieval-Augmented Generation (RAG).
• Awareness of Responsible AI, data governance, security and compliance requirements.
• Ability to translate technology capabilities into business outcomes and adoption.
• Experience delivering Data, Analytics and AI initiatives within Pharmaceutical R&D organizations.
• Familiarity with scientific data domains, including genomics, transcriptomics, proteomics, single-cell and multi-omics datasets, as well as related analytical and bioinformatics workflows.
• Experience supporting preclinical research initiatives such as target discovery, target validation and scientific evidence generation.
• Experience delivering data-driven and AI-enabled initiatives supporting Target Story, Indication Expansion and other research insight generation processes.
• Experience working with platforms supporting clinical development, laboratory data integration and research data management.
• Proven ability to collaborate with multidisciplinary teams including scientists, bioinformaticians, data engineers and business stakeholders.
• Strong understanding of FAIR Data Principles, scientific data governance and regulated cloud-based research environments.

Key Capabilities

• Strong business and value-oriented mindset.
• Product-focused approach with emphasis on adoption and outcomes.
• Ability to influence stakeholders and drive alignment across business and technology teams.
• Strong delivery, planning and prioritization skills.
• Collaborative leadership style with the ability to work effectively without direct authority.