Head of Product Analytics – Modelling

Overview

In this role you will lead Product Analytics to shape data-driven digital experiences for Experian’s direct-to-consumer products. You will own the analytics roadmap, partner with Product, Design and Engineering, and drive customer insights, predictive modelling and AI-enabled decisioning to improve engagement, retention and lifetime value. You’ll manage a high-performing team and embed analytics throughout the product lifecycle to accelerate innovation. This is a strategic, cross-functional role with a clear impact on product strategy and commercial outcomes.

Pay / Benefits

• Hybrid working – 40% office-based
• Competitive compensation and discretionary bonus
• Pension
• Bupa healthcare
• Sharesave scheme
• 25 days annual leave + 8 bank holidays + 3 volunteering days

Responsibilities

• Own and align the Product Analytics roadmap with product strategy and commercial objectives
• Collaborate with Product Managers, Designers and Engineers to embed analytics across the product lifecycle
• Lead customer journey analytics to improve engagement, conversion, and retention across web and app
• Develop predictive models and analytical solutions (e.g., Next Best Action, recommendations, intelligent decisioning)
• Influence product strategy via customer insights, behavioural analytics and opportunity sizing
• Support launches with measurement frameworks, experimentation, and post-launch evaluation
• Champion experimentation and AI-driven approaches to optimize customer value and product performance
• Collaborate with Marketing, Data Science, Data Engineering and Analytics teams to leverage segmentation and scalable data solutions

Key requirements

• Proven experience leading Product, Digital or Customer Analytics teams
• Strong track record partnering with Product leadership to influence strategy and roadmaps
• Experience building predictive models and solutions like Next Best Action, propensity models or recommendation engines
• Expertise in behavioural analytics, journey analysis, experimentation and A/B testing
• Advanced SQL skills and experience with large-scale datasets
• Strong commercial acumen translating insights into engagement and lifetime value improvements
• Experience establishing product performance frameworks, KPIs and measurement strategies
• Experience using AI, automation and advanced analytics for product innovation

• commercial acumen
• strategic influence
• cross-functional collaboration
• predictive modelling
• Next Best Action
• propensity models

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