About You
Staff Data Engineer (all genders)
Hamburg, HH, Germany · Posted 1 day ago
Tech Stack
SQL PythonRDagster
Language Requirements
English (required)German (not_required)
Requirements
Staff Seniority
7+ years Experience
No Degree
Remote Policy
On-site
Company Description
Job Description
- Development and evaluation of statistical models and algorithms for complex marketing issues
- Independent analysis of complex data with the aim of identifying new insights and potential for performance optimization
- Identifying direct and indirect correlations between relevant key figures and deriving recommendations for action
- Linking and using the content of data from tracking systems and other reporting sources
- Support in the further development and testing of performance-relevant (attribution) models
- Initiation and further development of prediction and classification models using machine learning algorithms
Qualifications
- You bring at least seven years of hands-on experience in Data Science, ideally in an agency, e-commerce, or performance-driven environment
- You have initial experience with machine learning algorithms and a solid understanding of common data analysis methods such as regression and clustering; knowledge of marketing attribution models is a strong plus
- You are proficient in SQL and either Python or R (both are a bonus)
- Experience with Dagster or comparable data orchestration tools is highly appreciated
- You are naturally curious, enjoy exploring new topics, statistical methods, and emerging technologies, and stay up to date with current technical developments
Additional Information
Your perks at a glance: Visit our benefits page.
Simply apply online via our career page - we will get back to you as soon as possible!
A Place Where You Can Be You
We take it as our responsibility to create an environment where everyone feels welcome, exactly as they are.
Different backgrounds and perspectives make us stronger and shape our culture in ways that matter.
What we stand for internally, we stand for as a brand: acceptance, inclusion, and a fairer approach to fashion.