Strategic Analytics & Programme Delivery Lead

Strategic Analytics & Programme Delivery Lead

Focus: Cyber Risk Quantification & Executive Decision Support

Engagement: High-Visibility Global Enterprise Consulting Programme

The Role

We are seeking an experienced Programme Delivery Lead to own the end-to-end delivery of a major Cyber Risk Quantification (CRQ) programme for a global enterprise client. The role combines large-scale programme delivery, Agile product management, executive stakeholder engagement and data storytelling. You will work closely with the CISO and senior leadership to shape the solution, manage delivery and coordinate a multidisciplinary team across research, quantitative analysis, data engineering and Power BI.

Key Responsibilities

Programme & Delivery Leadership

• Own delivery of a complex, multi-year enterprise analytics programme.
• Lead governance, scope, milestones, dependencies, risks, quality and stakeholder management.
• Run the programme using Agile methodologies, including backlog management, prioritisation, sprint planning, user stories and acceptance criteria.
• Coordinate multidisciplinary workstreams and maintain high delivery standards.

Executive Stakeholder Management

• Partner with the CISO and senior leadership to define priorities, decision requirements and risk appetite.
• Lead workshops and translate strategic objectives into clear requirements.
• Manage expectations, trade-offs and executive communications throughout delivery.

Product & Decision Framework

• Own the product vision and delivery backlog.
• Work with the CISO to develop and operationalise the CRQ decision framework.
• Translate analytical outputs into clear user journeys, decision points and executive narratives.
• Provide direction on information hierarchy, wireframes and visual storytelling.

Enterprise Discovery

• Direct research across the organisation to understand the enterprise landscape and gather the information required by the programme.
• Guide questionnaires, stakeholder interviews and evidence collection.
• Identify information gaps and ensure findings are converted into actionable requirements.

The Team

You will lead a multidisciplinary team including:

• Quantitative Analysts – probabilistic modelling, simulations and analytical methodology.
• Enterprise Researchers – organisational discovery, questionnaires and information gathering.
• Data Engineers – data sourcing, integration and ingestion.
• Power BI Developers – implementation of analytics, dashboards and decision-support experiences.
• Client SMEs and stakeholders – business, cybersecurity and organisational expertise.

The Ideal Candidate

• Proven delivery of large-scale enterprise technology, data, analytics or BI programmes, including multi-year engagements of €1m+.
• Strong consulting experience with C-suite and senior enterprise stakeholders.
• Hands-on experience leading Agile delivery and managing product backlogs.
• Experience delivering analytics or BI solutions with Power BI teams.
• Experience coordinating multidisciplinary teams across research, data engineering, analytics and technology.
• Strong product mindset with the ability to turn ambiguous requirements into an executable solution.
• Excellent communication, facilitation and visual storytelling skills.
• Strong analytical literacy and the ability to translate complex quantitative outputs into clear business implications.

Desirable

• Experience in cybersecurity, cyber risk, operational risk or enterprise risk.
• Exposure to CRQ or quantitative risk methodologies.
• Experience with executive dashboards or decision-support products.

What Success Looks Like

Success means delivering an end-to-end CRQ framework for a clearly defined set of priority risk scenarios. The solution will combine enterprise discovery, quantitative analysis, data engineering and executive reporting into a working operational capability, with automated or real-time data ingestion and updates where appropriate. The result should provide the CISO and senior leadership with a trusted, current and repeatable view of cyber risk that supports material risk and investment decisions.