Analytics Manager, Marketing Analytics

About the role

The Analytics Manager, Marketing Analytics defines the analytics strategy and leads the execution of marketing measurement at scale across the organization. This position acts as the primary analytics partner for senior business and product leaders within the Marketing domain, guiding how data influences key choices. The role translates complex analysis into clear recommendations and ensures that insights drive concrete follow-through and measurable outcomes. Success is determined by the ability to turn raw marketing data into narratives that influence strategic direction. The manager is responsible for establishing a coherent vision for how marketing performance is measured and reported. They own the governance of analytics practices to ensure consistency and reliability across markets. This position requires fluency in both the technical foundations of marketing data and the commercial context of a global business. The role ultimately shapes how the organization understands and optimizes its marketing impact.

Key facts

What you'll do

Define the end-to-end analytics roadmap for the Marketing domain, prioritizing initiatives that address the most critical business questions.

Lead a team of data scientists, providing guidance on methodologies, code quality, and the practical application of analytics to marketing problems.

Own the design and implementation of key performance indicators that measure the business outcomes of marketing initiatives.

Partner closely with Marketing, Product, and Strategy & Operations to shape measurement frameworks and influence tactical decisions.

Champion experimentation and attribution practices, ensuring that insights from tests and media mix modeling directly inform resource allocation.

Mentor data science team members, focusing on skill development, career growth, and the delivery of high-standard analytical work.

Translate complex analytical findings into clear narratives and visualizations that drive decision-making and stakeholder alignment.

Establish governance and best practices for marketing analytics to ensure consistency, reliability, and scalability across all operating markets.

Apply statistical analysis and coding skills in SQL and Python or R to solve ambiguous problems and validate business hypotheses.

Continuously evaluate the impact of marketing analytics work, ensuring that analysis leads to measurable improvements in business performance.

Requirements

You have performed Data Analytics or Data Science for 6+ years, with at least 2 years of experience in a leadership role managing other analysts or data scientists.

You have led large teams of 5-10 direct reports, demonstrating the ability to manage capacity, performance, and professional development.

You hold a Bachelor's degree, and your background includes strong foundations in statistics, coding, and data interpretation.

You are skilled in using SQL to query large datasets and Python or R for statistical analysis and data manipulation.

You understand core concepts such as experimentation, attribution, media mix modeling, and marketing measurement, and you apply them pragmatically.

You have a track record of turning analysis into decisions, actions, and clear business impact through communication and partnership.

You can operate effectively in a fast-paced environment where geolocational and temporal data are handled in real-time across cities with differing economics.

You bring the ability to mentor and hire skilled data scientists, contributing to the strength and health of the analytics team.

You communicate complex ideas clearly to both technical and non-technical audiences, aligning stakeholders around measurement strategy.

Nice to have

Experience in building and maintaining analytics roadmaps specifically for marketing-focused data products.

Deep familiarity with marketing-specific measurement techniques such as incrementality testing and multi-touch attribution.

Background working with geolocational and real-time data streams in a multi-market operational environment.

Experience leading data science teams in a fast-growth, high-impact consumer or marketplace business.

Practical notes

This role operates in a fast-paced environment with geolocational and temporal data in real-time and differing city economics and dynamics.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Analytics managers operate at the intersection of data and business strategy. They rely heavily on SQL, statistical methods, and experimentation frameworks. Collaboration across functions is central to aligning measurement with business goals. The role involves both strategic planning and hands-on analysis. Continuous learning is essential in a data-driven environment.

Questions to ask

Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

About the company

Wolt

English is hiring for Analytics Manager, Marketing Analytics. Berlin, Germany; Helsinki, Finland; London, United Kingdom; Stockholm, Sweden.