Principal Decision Scientist - Marketing

As a Principal Decision Scientist - Marketing, you will lead the development of an analytics function that transforms complex, cross-channel data into strategic insights and measurable business impact. You'll shape the technical direction for advanced analytics initiatives, driving sophisticated modelling, experimentation, and data infrastructure capabilities that support smarter decision-making across the organization.

What you'll do

• Lead the design and execution of experimentation frameworks, including geo-based and holdout incrementality testing, to rigorously validate marketing investment decisions at scale
• Evolve the organisation's Marketing Mix Modelling (MMM) capability, including model development, calibration, and translation into actionable budget allocation recommendations for senior leadership
• Develop sophisticated statistical models such as LTV prediction, churn scoring, and audience segmentation that influence strategic decisions across Marketing, Finance, and Product
• Architect and govern the marketing data layer, ensuring best practice across dbt modelling, data quality, and documentation
• Define and lead cross-functional analytics initiatives that span teams and business units, bringing structure and analytical rigour to ambiguous, high-stakes commercial problems
• Translate highly complex findings into compelling strategic narratives and executive-ready recommendations, enabling data-driven decisions at the leadership level
• Partner with Finance (FP&A) to ensure marketing efficiency metrics, budget frameworks, and unit economics (CAC, LTV, Payback Period) are consistent with company-wide financial reporting and planning
• Lead the team's thinking on how AI tools and techniques can augment the analytics workflow, and act as a practical guide for marketing teams on where and how AI can meaningfully improve their ways of working

What you'll need

• 8+ years of experience in a similar role
• Deep expertise across Acquisition (Paid Search, Paid Social, SEO) and Retention (CRM, Lifecycle, Churn), with the ability to connect channel-level performance to business-wide outcomes
• Proven, hands-on experience building and deploying Marketing Mix Models (MMM) and incrementality testing frameworks (geo-based, holdout, synthetic control) in a real business context
• Proficiency in applied statistical modelling, such as LTV modeling, predictive scoring and causal inference techniques
• Advanced Python or R for statistical analysis, modelling, and automation, with production-quality code standards
• Demonstrated experience architecting scalable data models using SQL and dbt within a modern data stack
• Exceptional ability to distil complex technical findings into clear strategic narratives for non-technical stakeholders and senior leadership
• Experience working within a high-growth SaaS or digital business with an understanding of unit economics (CAC, LTV, Payback)

Nice to have

• Practical experience applying AI tools to accelerate, enhance and automate analytical workflows
• Demonstrated experience mentoring and developing analysts including coaching on technical skills, analytical thinking and stakeholder engagement
• Exposure to product analytics or growth functions, with an ability to connect marketing and product data across the funnel

What they offer

• Flexible hours and wellness perks
• 28 paid leave days plus well-being days and compassionate leave
• Performance-based bonuses and paternal leave
• Mentorship, coaching, and internal mobility opportunities
• Inclusive, collaborative team environment