Senior Data Scientist (m|f|d)

Are you passionate about using data to drive real business impact — and equally excited about shaping how Data Science is lived and breathed in a company? We are looking for a Senior Data Scientist (m/f/d) who not only thrives in applying cutting-edge methods and technology hands-on but also helps build a Data Science mindset across the organization.

We are a leading e-commerce company with around 700 employees, at an exciting stage: growing, ambitious, and ready to evolve. We are on our journey towards greater data maturity and recognize the need to change. Data Science is seen as a critical enabler — but we need curious, capable people like you to help make it happen.

This role combines technical excellence with cultural leadership, offering you the opportunity to apply your expertise while shaping how Data Science is embedded across teams. You’ll help shape both the technical foundations and the organizational conditions needed for impactful Data Science. You’ll join at an exciting moment, with the opportunity to shape and co-create our growing Data Science capability.

Your Challenge — Are You Up for It?

Be part of building a technically strong, business-relevant Data Science team and influencing hiring, onboarding, and growth. Help establish best practices, technical standards, and a shared understanding of Data Science across the company. Collaborate with Product, Engineering, and Business teams to make data-driven decisions the norm. Obtain buy-in from senior stakeholders and managers to pivot the organization towards fast, data-driven decision-making.

About your new role

• Advocate for data-driven thinking and, together with your peers, contribute to building a sustainable Data Science practice.

• Partner closely with Data Science, Software Engineering, Product, and Business teams to turn prototypes into scalable, reliable solutions.

• Enable and mentor others to build, deploy, and monitor production-ready models using state-of-the-art technologies, including container technologies such as Docker.

• Collaborate with the owners of the existing experimentation program to refine and scale causal analysis and experimentation frameworks that generate actionable insights.

• Foster knowledge-sharing, mentor colleagues, and act as a trusted advisor for stakeholders across the organization.