Head of Data - Canada Life Reinsurance

Head of Data \- Canada Life Reinsurance

Location:Dublin, IE
Company: Canada Life Group Services
Description:Full Time Permanent position

Hybrid role based in our City Centre offices

What we offer

We have embraced a hybrid working model for most of our positions, which means that you can enjoy a balanced approach of working from home for part of the week and working from the office for the remainder of the week.

We offer a comprehensive benefits package including competitive salaries and bonuses, robust Learning and Development support, excellent Defined Contribution pension and comprehensive Wellbeing initiatives and support to name but a few.

Further details on our benefits package can be accessed here Benefits (life\-careers.com)Role Overview

This is a critical new leadership role with responsibility for shaping and delivering CLRe’s global data and AI agenda. Working across a complex global reinsurance business, the Head of Data will define, build and deliver a modern data and AI value\-led capability from first principles, aligned to the business strategy and regulatory environment. The Head of Data will establish a scalable, trusted and business\-led data function, enabling improved decision\-making, efficiency, control and growth. This includes defining the data and AI strategy, contributing to the construction of the target operating model, and delivering practical, high\-value use cases that demonstrate measurable impact across all aspects of the business.

Reporting directly to the VP, Head of Operations and Technology, with a mandate sponsored by the CLRe Executive leadership team, the individual will work in close partnership with Actuarial, Finance, ALM, Pricing, Operations and HR. The role will involve international travel.

Scope

• Build and lead a high\-performing Data \& AI team, with responsibility to scale over time


• Matrix leadership across business division, influencing senior stakeholders and divisional leads


• Close collaboration with key stakeholders across CLRe’s global leadership teams and regions (Technology, Actuarial, Finance, ALM, Pricing, Operations and HR)


• Engagement with Group / Regional Data \& AI leadership

Data \& AI Strategy and Vision

• Define a practical, multi\-year data and AI strategy aligned to CLRe’s business priorities


• Translate complex business needs into a clear, phased data and AI agenda, balancing quick wins with longer\-term capability building


• Work with the business to identify and prioritise the domains where data and AI will matter most (e.g. Actuarial, Finance, Risk, Operations)


• Ensure alignment with Group / Regional data and technology strategies

• Assess the current data landscape, including quality, risks, dependencies and technical constraints


• Define and implement a phased plan to improve data architecture, quality, consistency and reliability


• Establish data ownership, stewardship and accountability frameworks across the organisation


• Develop core data management capabilities, including metadata, lineage and data catalogue


• Identify and remediate key data risks, control gaps and legacy dependencies, ensuring alignment with regulatory expectations

• Define and embed a value\-led prioritisation framework for data \& AI initiatives


• Build and deliver an initial portfolio of high\-impact use cases that demonstrate tangible business outcomes, and ROI


• Ensure clear business ownership and accountability for benefits


• Track and report realised value (e.g. efficiency, cost reduction, revenue enablement, risk reduction)


• Scale proven use cases across the organisation, with repeatable delivery patterns and playbooks

• Define the target data architecture and platform strategy, aligned to enterprise standards


• Lead technology selection decisions (where required), including evaluation criteria and vendor engagement


• Ensure a scalable, secure and cost\-effective data platform foundation (e.g. cloud, data hub, integration)


• Balance pragmatic reuse of existing capabilities with targeted investment

• Define a clear and practical AI ambition, aligned to business priorities and risk appetite


• Identify and deliver well\-governed AI use cases that enhance productivity, insight and decision\-making


• Establish safe environments for experimentation, prototyping and learning


• Ensure robust and proportionate frameworks for AI governance, transparency, privacy and human oversight


• Integrate AI capabilities into core business workflows, not standalone tools


• Define AI standards and patterns (model lifecycle, monitoring, human‑in‑the‑loop) to support repeatable adoption

• Design and implement the data \& AI operating model, including structure, roles and ways of working


• Establish a federated model balancing central expertise with domain ownership


• Define demand management, prioritisation and delivery governance processes


• Build and lead a high\-performing, scalable Data \& AI team, including hiring, development and performance management


• Ensure effective integration with Group / Regional data and technology capabilities

• Partner closely with senior stakeholders across business and functional areas


• Translate complex data and AI concepts into clear, business\-relevant outcomes


• Build trust and credibility in data and AI through practical delivery and transparency


• Lead organisational change to embed data\-driven decision making


• Design and deliver a data literacy and AI capability uplift programme across the organisation


• Establish consistent stakeholder routines (SteerCo cadence, communications, engagement) to drive adoption and decisions

• Establish proportionate and effective data governance, controls and risk frameworks


• Ensure alignment with relevant data protection, regulatory and compliance requirements (e.g. EU\-AI Act, model governance)


• Support internal and external audit, regulatory engagement, and control assurance processes


• Ensure data and AI initiatives are delivered in line with risk appetite and regulatory expectations


• Maintain clear policy\-to\-practice traceability (controls mapped to standards; evidence maintained for assurance)

We are seeking a commercially minded and pragmatic data leader who can build and deliver a modern data capability within a global reinsurance business. The successful candidate will combine strategic thinking with a strong bias to delivery and will be comfortable setting direction while working collaboratively across established, technical teams.

Strategic Capability

• Strong ability to translate business priorities into a clear, pragmatic data \& AI strategy


• Sound judgement in sequencing initiatives and balancing long\-term capability build with near\-term delivery


• Focus on business outcomes and value creation, not technology for its own sake


• Pragmatic and delivery\-focused, with a strong bias towards progress and execution

• Significant experience in data, analytics, AI or technology transformation roles, ideally within reinsurance, insurance or regulated financial services


• Experience defining enterprise\-level data strategies, operating models and governance frameworks


• Practical understanding of modern data platforms and AI capabilities, with a focus on applied use


• Demonstrated ability to deliver outcomes with imperfect data and technical constraints

• Track record of delivering tangible, measurable business outcomes in complex, multi‑stakeholder organisations


• Proven ability to define, measure and track value from data‑led initiatives


• Experience embedding value tracking and benefits realisation disciplines

• Excellent communication skills, able to explain complex data and AI concepts in clear, business‑relevant terms


• Proven ability to influence across functions, regions and seniority levels through collaboration and well‑reasoned challenge


• Strong credibility with both technical and business audiences

• Experience building and leading data and analytics teams


• Strong coaching and development capability


• Collaborative leadership style with high personal accountability

• Good, practical understanding of data governance, controls and regulatory environments


• Experience operating within regulated financial services environments preferred


• Awareness of supervisory, audit and regulatory expectations relevant to data and AI

• Experience delivering data strategy in complex, multi\-stakeholder organisations


• Track record of building or materially reshaping data capabilities, operating models or platforms


• Experience selecting and implementing data and analytics technologies, including working with vendors and internal technology teams


• Strong understanding of governance, controls and data management in regulated environments


• Experience working with actuarial, finance, risk, underwriting or similarly technical stakeholder groups


• Experience identifying and delivering practical AI or automation use cases in business settings


• Bachelor’s degree required

• Defined and agreed data \& AI strategy and roadmap


• Established core data foundations and governance frameworks


• Delivered initial portfolio of high\-value use cases with measurable impact


• Built a credible, high\-performing Data \& AI function


• Est

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