Staff Decision Scientist

About the role

The operates as a critical strategic partner embedded directly within product, engineering, marketing, and finance teams. You are responsible for owning the complete analytical narrative for your operating group, ensuring that insights translate into concrete changes in roadmaps and resource allocation. This role focuses on producing decisions rather than merely maintaining dashboards or reports. You will define the tools and workflows that allow automation to manage volume, paving the way for an AI-native organization while the team concentrates on deeper analytical work. Your primary instruments are statistical inference, clear thinking, and the judgment required to identify the most critical questions that move the business forward. You will report into the Data & Analytics leadership team and work closely with data engineers, data scientists, and ML engineers to ensure alignment and impact.

Key facts

What you'll do

• Own the analytical narrative for your Operating Group (OG), serving as the strategic thought partner across cross-functional teams including product managers, engineers, marketers, and finance specialists, setting the agenda for the highest-use questions the OG should address.
• Tell stories that move teams to action by presenting to leadership and working teams with clear narratives and a defined point of view, ensuring that a great insight does not remain a failed insight due to inaction.
• Establish causality with the right tools for the situation, including A/B testing, analytics, and causal inference, while collaborating with engineering to implement event instrumentation and with Product to translate insights into concrete action.
• Define metrics strategies that measure what truly matters, working backward from how users experience the product to develop and implement measurement frameworks for your OG within a complex ecosystem featuring multi-user engagement and numerous interaction methods.
• Build explanations on top of measurement, always grounding analysis in the reality that users are people with motivations and context that data alone cannot reveal.
• Shape the AI-native analytics stack by leading the evaluation and adoption of new tools, agent workflows, and practices that enable self-serve capabilities across the OG and transition the team from reactive to proactive to autonomous.
• Mentor senior ICs on causal thinking, experimental rigor, and AI-leveraged workflows, raising the ceiling of the craft within the organization.

Requirements

• Problem-solving mindset: You structure ambiguous problems precisely before reaching for a tool, AI or otherwise, ensuring clarity of thought and approach.
• Ownership mentality: You take responsibility from framing the question through delivering the recommendation and tracking its impact, being accountable for decisions changed rather than only analyses delivered.
• AI-native working style: You use AI tooling (Claude Code or equivalent) as a genuine development partner, delegating discrete tasks, reviewing outputs critically, and running parallel workstreams to increase efficiency.
• Curiosity and initiative: You do not wait for the roadmap to tell you what to analyze; you dig into data because you are genuinely curious about how things work and uncover new insights.
• Influence at scale: You have shaped strategy at the business unit level by framing the right question and making the evidence impossible to ignore, driving meaningful change across teams.
• 8+ years in an analytics, data science, or decision science role at a consumer tech company, providing a deep foundation of experience in fast-paced, user-centric environments.
• Advanced degree in a quantitative field such as economics, statistics, quantitative social science, or operations research, or equivalent practical experience that demonstrates rigorous analytical capability.
• Demonstrated experience with causal inference methods in applied settings, including difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, and propensity score matching, ensuring robust conclusions.
• Track record of influencing product or business strategy through data, with specific examples of cross-functional impact that highlight your ability to drive decisions and execution.
• Comfort working within a complex ecosystem involving multi-user engagement and numerous interaction methods, allowing you to design measurement frameworks that reflect real-world complexity.
• Strong storytelling and presentation skills that enable you to communicate insights clearly to both technical and non-technical audiences, ensuring understanding and action.
• Collaboration mindset that supports effective partnerships with data engineers, data scientists, and ML engineers to integrate analytical outputs into production systems and product decisions.

Practical notes

This role operates in a hybrid model centered in London, allowing for remote work weeks alongside in-person/office meetings.