Customer Data Analyst (Customer Segmentation) (all genders)

THE ROLE & THE TEAM

You work for the Customer Analytics team in Zalando’s Markets organization, which enables data driven business strategies for 20+ countries. Through our customer focussed analytics and segmentations we put our customers at the center of every marketing and retail decision. As a (Senior) Customer Data Analyst in our Customer Segmentation Team you are the closest link to our customer: You build a deep understanding of our customer base by developing and analyzing different customer segments based on their purchasing behavior, interests, customer value and onsite activities. You will transform data and segmentations into actionable insights and recommendations that drive strategic decisions and customer retention.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Develop and analyze customer segmentations and audiences, support targeting and steering initiatives to drive customer value and retention. Collaborate with data scientists and engineers to optimize and productionalize your segmentations and audience selections.
• Design, conduct and evaluate A/B tests to optimize your segmentations and audiences according to their use case. Recommend testing strategies to optimize targeted campaigns, campaign efficiency and ultimately customer value and retention. Translate complex questions into sound analytical tasks, autonomously planning large scale projects.
• Collaborate with business stakeholders to identify new strategic opportunities and recommend actions supporting the customer strategy. Present your findings and work closely with business stakeholders and product owners to operationalize your recommendations.
• Drive data mindset in the team and provide senior guidance to your team members in terms of methodology & technology to raise the bar within the department. Collaborate with other analysts, data scientists, engineers and commercial colleagues to untap new sources of data and know-how. 
• Independently manage analytical projects, identifying efficiency opportunities and supporting decision-making with insights from descriptive and inferential analysis.
• Conduct knowledge-sharing sessions, support junior colleagues, and contribute to internal events and the hiring process.

WE’D LOVE TO MEET YOU IF

• You have 3+ years experience in using customer data in smart and creative ways to answer business questions and/or drive targeting efforts incl. model driven statistical analysis, e.g. Causal Inference. Very good quantitative degree, e.g. in Economics, Statistics, Mathematics, Computer Science. 
• Advanced skills in data methodologies and technologies (Python and SQL, PySpark). Visualization tools, e.g. MicroStrategy, Tableau, PowerBI and versioning tools, e.g. Git/GitHub, are considered a plus. Curious about learning new technologies, e.g. Databricks, AWS data lake, Airflow.
• Strong communicator to challenge the status-quo, tell data stories, maximize decision impact of your results and liaison with commercial and tech people alike.
• Proactive, fast learner, problem solver, teamplayer, comfortable working in English in a fast paced international work environment

INCLUSIVE BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring – we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.

do.BETTER – our diversity & inclusion strategy:

https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy

Our employee resource groups:

https://corporate.zalando.com/en/our-impact/our-employee-resource-groups

Recruiter

Stanislava Zapototska

[email protected]

Please note that all applications must be completed using the online form – we do not accept applications via e-mail.

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