B. End-to-End Project Delivery

• Lead Data, Analytics and AI projects from initiation and discovery through design, build, deployment, adoption and operational handover.
• Coordinate cross-functional delivery teams composed of business, data, analytics, AI, engineering, architecture, security, compliance and change management contributors.
• Maintain an integrated project plan and ensure effective coordination across workstreams and delivery partners.
• Track project execution against the agreed scope, timeline, budget, quality and expected outcomes.
• Ensure timely escalation and resolution of delivery issues and cross-project dependencies.
• Adapt the delivery approach to the nature and maturity of each initiative, including proof of concept, MVP, industrialization, migration or enhancement projects.
• Ensure appropriate documentation and readiness for transition to operational support teams.

C. Project Governance, Risks and Financial Management

• Establish and operate fit-for-purpose project governance, including project team meetings, working groups, steering committees and decision forums.
• Prepare clear project status reports covering progress, achievements, milestones, budget, risks, issues, dependencies and decisions required.
• Maintain project risk, issue, action and decision logs and ensure that owners and resolution plans are clearly identified.
• Proactively identify delivery risks and implement mitigation or recovery plans.
• Monitor project expenditure and resource consumption against the approved budget and forecast.
• Support project financial planning, purchase order follow-up and vendor consumption monitoring, in coordination with the relevant finance and procurement contacts.
• Escalate material deviations and provide sponsors with clear options and recommendations.

D. Business Requirements, Data and Solution Coordination

• Facilitate collaboration between business stakeholders and Data & AI experts to translate business challenges into clear requirements and actionable project deliverables.
• Coordinate the definition and validation of business requirements, data requirements, use cases, user journeys and acceptance criteria.
• Ensure that analytical outputs, reports and Data & AI solutions are understandable, actionable and aligned with business needs.
• Coordinate data profiling and feasibility activities with the relevant data owners and technical teams.
• Ensure that data quality, data ownership, privacy, security, compliance and architecture requirements are addressed throughout the project lifecycle.
• Support business acceptance and ensure that delivered solutions meet agreed functional and non-functional requirements.
• Facilitate informed trade-offs between business value, delivery feasibility, time, cost and technical sustainability.

E. Stakeholder and Partner Management

• Build effective working relationships with business sponsors, business owners, Data & AI Product Delivery Leads, IT Business Partners and delivery teams.
• Act as the central coordination point for the projects assigned to the role, while ensuring clear accountability across business and technical contributors.
• Facilitate project workshops, decision-making sessions and governance forums.
• Communicate complex Data & AI topics in a clear and accessible manner to executive, business and technical stakeholders.
• Coordinate external partners and service providers involved in project delivery.
• Monitor supplier deliverables, dependencies, commitments and quality in line with agreed contractual responsibilities.
• Promote transparency, timely escalation and fact-based decision-making across project stakeholders.

F. Adoption, Handover and Continuous Improvement

• Incorporate adoption and change management activities into project planning from the outset.
• Coordinate communication, training, user readiness and stakeholder engagement activities with business owners and change management contributors.
• Monitor user adoption and the realization of expected project outcomes after deployment.
• Coordinate the transition of delivered solutions to the appropriate operational, platform or support teams.
• Capture project lessons learned and translate them into improvements to delivery methods, templates, governance and ways of working.
• Contribute to the definition and continuous improvement of common Data & AI project management standards.
• Share knowledge and reusable practices across the Data & AI community.

Knowledge & Experience

Knowledge & Experience (essential)

• 7+ years of experience in project or program management, including significant experience delivering Data, Analytics, Business Intelligence or AI initiatives.
• Proven experience leading complex, cross-functional projects involving business, data and technology stakeholders.
• Demonstrated ability to structure projects from initial demand and scoping through delivery, adoption and operational handover.
• Strong experience in project planning, governance, resource coordination, budget monitoring, risk management and executive reporting.
• Experience managing external partners, consultancies or technology service providers.
• Strong business acumen and ability to translate business objectives into clear, executable delivery plans.
• Strong data literacy and the ability to communicate effectively with business, executive and technical stakeholders.
• Excellent analytical, problem-solving, facilitation and stakeholder management skills.
• Ability to operate across multiple business domains and rapidly understand new functional contexts.
• Professional proficiency in English.

Technical Knowledge

• Solid understanding of Data, Analytics, Business Intelligence and AI project lifecycles.
• Good understanding of data architecture, data integration, data platforms, reporting, analytics and AI concepts.
• Ability to understand and challenge business requirements, solution options, estimates, plans and technical dependencies.
• Familiarity with Agile, iterative and traditional project delivery methodologies, with the ability to select a fit-for-purpose approach.
• Experience with project and collaboration tools such as Jira, Confluence and Microsoft 365.
• Understanding of data governance, data quality, privacy, security and compliance considerations.
• Ability to define and monitor project KPIs, delivery metrics and business outcome indicators

Knowledge & Experience (preferred)

• Experience in the pharmaceutical, life sciences or another regulated industry.
• Experience delivering projects across several business functions, such as Commercial, Medical, R&D, Finance, HR, Supply Chain, Quality or Corporate Functions.
• Familiarity with pharmaceutical data, regulatory and compliance requirements.
• Experience with cloud-based data and analytics platforms.
• Experience in change management and adoption of data-driven solutions.
• A recognized project or program management certification such as PMP, PRINCE2, AgilePM or equivalent would be an advantage.
• French language proficiency would be an advantage.

Education / Certifications (essential)

• Master’s degree or equivalent experience in Data, Information Technology, Computer Science, Engineering, Business Administration, Project Management or a related discipline.

Language(s) (essential)

• English

Language(s) (preferred)