Data Scientist - Marketing; f​/m​/d

You join our Analytics & Data Science team for Marketing, working alongside a second Data Scientist, Data Analysts, the Marketing Tech team and the Marketing business teams. You step in wherever the team needs you, with machine learning and data analysis as the equally weighted core. Your work shapes how customers discover our products on Google Shopping, price-comparison sites, and beyond.

We welcome all applications, but can only consider applications submitted online. Applications submitted by post will be disposed of for data protection reasons and will not be returned.

Turn business challenges into data-driven insight by understanding the real business question, digging into performance data to find the root cause, and translating it into clear, actionable recommendations for technical and non-technical audiences

Build robust machine-learning solutions in close collaboration with the product team and run them in production on our platform, raising the performance of our Marketing channels

Own your data products end to end, from spotting the opportunity through prototype and build to running them in operation. You care about the whole Marketing product, not just your model

Validate improvements by defining success metrics and analytical frameworks, and running experiments with the product team and Marketing business teams (e.g. A/B tests, causal inference, incrementality testing)

Work with web tracking and attribution data to build features, close measurement gaps, and sharpen our understanding of the customer journey

Shape our data-science practice together with the Senior Data Scientist and the wider Data Science Guild

In Data Science (if specifically in the field of marketing, 1+ years)

In Data Science, Computer Science, Statistics, or a related field

Mandatory

Strong Python skills and experience with machine-learning libraries such as PyTorch, scikit-learn, and XGBoost

Mandatory

Solid grounding in statistics and experimental design (e.g. A/B tests, causal inference): you are equally adept at building a model and carrying out an advanced ad-hoc analysis

Mandatory

Experience deploying and operating ML models in production with tools such as Docker, Kubernetes, Airflow, or Dagster, including monitoring and alerting

Mandatory

Experience with large datasets and advanced SQL (e.g. Big Query), and comfortable building and owning data pipelines with a transformation framework (e.g. Dataform, dbt) that feed reliable feature stores and data products

Mandatory

Strong communication skills and a proactive, self-directed way of working. You thrive in a team, working closely with product and cross-functional colleagues, and convey your results clearly and concisely to different stakeholder groups

Advantageous

Marketing know-how and hands-on web tracking experience (Google Tag Manager) are a strong plus

Mandatory

A willingness to challenge «how things have always been done» and propose more efficient, automated or effective solutions

Mandatory

Maintaining resilience and agility while adjusting strategies as needed

Cooperative, innovative, piratesque, responsible, ambitious – these five values are what we practice and preach.

We encourage everyone to think on their feet, and love it when they come up with bold or edgy ideas.

Simplicity is at our core. We avoid…