Staff Data Scientist, Marketing Analytics

About the Role

As a Staff Data Scientist supporting Wolt’s Marketing team, you will help shape how we use data to understand, improve, and scale our marketing investments. You’ll work on high-impact questions around growth, efficiency, customer acquisition, and marketing performance across Wolt’s markets. In this role, you’ll combine deep analytical expertise with hands-on collaboration, working closely with business teams to identify important opportunities, design robust measurement approaches, and guide decisions through data. From uncovering performance drivers to building scalable reporting, experimentation, and monitoring frameworks, you’ll help ensure we are focusing on the right opportunities and investing behind the ideas that truly work.

What you'll be doing

• Own marketing measurement: Help improve how Wolt measures paid marketing performance across channels, campaigns, markets, and customer segments.
• Turn data into decisions: Analyze marketing performance to identify what is driving growth, where spend is efficient, and where teams should adjust investment or execution.
• Improve attribution quality: Develop practical ways to evaluate attribution, understand its limitations, and make performance reporting more accurate, trusted, and useful.
• Build scalable foundations: Create dashboards, analyses, experimentation approaches, and monitoring frameworks that help marketing teams make better decisions faster.

You’ll move fluidly between hands-on analysis and business partnership, ensuring we don’t just report on marketing performance, but use data to improve how we invest, learn, and scale.

Our humble expectations

• 6+ years of experience in an analytics, data science, marketing analytics, growth analytics, or other quantitative role.
• Proficiency in SQL, Python/R, and AI IDE tools, with the ability to work confidently with complex and imperfect business data.
• Hands-on experience analyzing marketing, growth, marketplace, consumer, or performance data to guide practical business decisions.
• Experience with experimentation, attribution, and measurement concepts, with the ability to apply them pragmatically in real-world business settings.
• Strong communication and business partnering skills, with the ability to structure ambiguous questions and drive work from analysis through recommendation.