Data & AI Project Lead

Title:

Data & AI Project Lead

Company:

Ipsen Pharma (SAS)

 

About Ipsen:

Ipsen is a mid-sized global biopharmaceutical company with a focus on transformative medicines in three therapeutic areas: Oncology, Rare Disease and Neuroscience. Supported by nearly 100 years of development experience, with global hubs in the U.S., France and the U.K, we tackle areas of high unmet medical need through research and innovation.

 Our passionate teams in more than 40 countries are focused on what matters and endeavor every day to bring medicines to patients in 88 countries. We build a workplace that champions human-centric leadership and fosters a culture of collaboration, excellence and impact. At Ipsen, every individual is empowered to be their true selves, grow and thrive alongside the company’s success. Join us on our journey towards sustainable growth, creating real impact on patients and society!

For more information, visit us at https://www.ipsen.com/ and follow our latest news on LinkedIn and Instagram.

Job Description:

Job Title: Data & AI Project Lead

Division / Function: GDIT – Global Data & AI Division

Manager’s Job Title: Head of Data & AI Product Management and Delivery

Ipsen Job Profile: Data Analytics

Location: Paris / London

WHAT - Summary & Purpose of the Position :

The Global Digital IT (GDIT) division is dedicated to being the business partner of choice for digital, data, and technologies, delivering outstanding value at speed and scale for patients and Ipsen. In this transformative context, GDIT plays a crucial role in driving innovation and efficiency across the organization.

Within GDIT, the Global Data & AI Division was established with the mission to act as a business enabler. This department is responsible for driving the strategic use of Data and AI across Ipsen and enhance business interoperability.

The Data & Analytics Manager leads the end-to-end delivery of cross-functional Data, Analytics and AI projects. The role is not permanently assigned to a specific business domain and may be deployed across different initiatives based on business priorities, project complexity and portfolio needs.

Working closely with business sponsors, Data & AI Product Delivery Leads, IT Business Partners, technical teams and external delivery partners, the Data & Analytics Manager translates project objectives into structured delivery plans and coordinates execution from initial scoping through implementation, adoption and operational handover.

The role ensures that projects are delivered in line with their agreed scope, timeline, budget, quality, security and compliance expectations, while maintaining clear governance, proactive risk management and effective stakeholder communication.

Key responsibilities include:

• Lead the end-to-end delivery of Data, Analytics and AI projects across business domains.
• Structure project scope, objectives, governance, delivery plans, resources and budgets.
• Coordinate business, functional, data, technology and external delivery teams.
• Monitor delivery progress, dependencies, risks, issues, decisions and project financials.
• Ensure that business requirements are translated into feasible and valuable Data & AI solutions.
• Communicate project status, outcomes and business impact to sponsors and stakeholders.
• Support solution adoption and coordinate transition to operational teams.
• Contribute to the continuous improvement of Data & AI project delivery standards and practices.

WHAT - Main Responsibilities & Technical Competencies
A. Project Scoping and Planning

• Work with business sponsors, Data & AI Product Delivery Leads and IT Business Partners to clarify project objectives, expected outcomes, scope and success criteria.
• Structure projects into clear phases, milestones, deliverables and decision points.
• Define project governance, delivery approach, resource requirements, budget assumptions and implementation plans.
• Coordinate the assessment of business requirements, data availability, functional feasibility, technical options, architecture implications and delivery scenarios.
• Ensure that assumptions, constraints, dependencies and responsibilities are clearly documented and agreed by the relevant stakeholders.
• Establish measurable project outcomes and value indicators in collaboration with business owners.

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.

HOW - 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)

• French

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