Senior Product Analytics & Experimentation Lead - MADRID

Project context

Our organisation is at a stage where data-driven decision-making is central to product growth and commercial success. However, the increasing complexity of our data ecosystem and product analytics needs requires a highly advanced, hands-on expert who can operate across both technical depth and commercial impact.

We are seeking an external expert with 5+ years of advanced analytics experience, ideally backed by a strong quantitative MSc or PhD, to strengthen our capability in translating ambiguous business challenges into structured analytical solutions. This role is critical in bridging the gap between raw data and actionable product strategy.

The external will operate in a highly cross-functional environment, partnering closely with product, engineering, and data teams to ensure analytical work is not only robust but also scalable, automated, and embedded into decision-making systems.

Goals and deliverables

The external engagement is expected to deliver impact across four core areas:

1. Analytical Problem Solving & Commercial Insight Generation

• Translate complex, ambiguous business questions into structured analytical frameworks

• Perform deep-dive analyses using SQL and Python to identify key drivers of performance

• Apply rapid estimation techniques and simulation approaches to prioritize high-impact opportunities

2. Product Analytics & Experimentation Leadership

• Define and maintain core product metrics and KPI frameworks

• Design, execute, and evaluate A/B tests and other experimental methodologies

• Ensure robust measurement of user journeys and product performance

3. Scalable Decision Systems & Data Products

• Develop and maintain dashboards and decision-support tools (e.g., Power BI, Looker)

• Move beyond reporting to build intuitive, scalable data products that support decision-making

• Collaborate with Data Engineers to automate and productionize analytical workflows

4. Cross-functional Leadership & Capability Building

• Act as a force multiplier within the team through mentorship and knowledge sharing

• Build strong cross-functional relationships with product, engineering, and commercial stakeholders

• Drive a culture of analytical rigor, ownership, and data-driven decision-making

Skills

Defining KPIs, designing A/B tests, analyzing experiments, and interpreting user behavior

SQL & Python Analytics

Ability to turn ambiguous business problems into structured analytical frameworks

Solid grounding in statistics, hypothesis testing, causal inference, and experimental rigor

Power BI / Looker