We are one of Europe’s leading providers in the field of live commerce, offering the most entertaining way to shop as a media platform. With our curated product portfolio spanning fashion, jewelry, beauty, wellness, household, and home & living, we inspire countless viewers, fans, and followers every day across all channels – on TV, in our online shop, and on social media. By seamlessly connecting lifestyle themes and brand worlds, we are driving innovation in cross-channel shopping entertainment. Our customers decide when and where they want to shop with HSE.
What you can expect:
- You develop innovative Predictive Models and Customer Behavior Analytics to optimize the Customer Journey in our dynamic E-Commerce and TV-Shopping environment
- You work with cutting-edge Machine Learning algorithms in Python and R, conduct Statistical Analysis, and create Feature Engineering for complex customer data models
- You implement A/B Testing frameworks, Causal Inference methods, and Statistical Modeling to validate Business Impact and customer behavior patterns
- You optimize Customer Analytics for LTV enhancement, Retention improvement, and Conversion maximization through advanced Data Science techniques
- You create predictive, inferential, and prescriptive models based on diagnostic modelling insights to explain and forecast customer behavior and business outcomes.
- You translate model outputs into measurable business actions in close collaboration with Marketing and Product teams.
- You collaborate closely with Engineering teams to integrate Predictive Analytics models into productive Business Intelligence systems and develop scalable data-driven solutions
Your profile:
- You have a successfully completed degree in Data Science, Statistics, Computer Science, Business Informatics, or comparable quantitative education with strong Machine Learning focus
- You bring solid experience in Statistical Analysis with Python or R and Supervised and Unsupervised Learning techniques for Customer Behavior Predictive Modeling
- You possess practical expertise in Feature Engineering, Model Evaluation, Performance Validation, and know modern Machine Learning libraries like scikit-learn, pandas, and statsmodels
- You have proven experience in productive machine learning models scenarios, Customer Analytics, and Data-driven Decision Making, ideally in E-Commerce or retail environments
- You demonstrate strong analytical thinking for Customer Intelligence, Retention Analytics, and LTV Optimization as well as experience with Experimentation frameworks
- You speak fluent English and ideally German, work solution-oriented in agile Data Science teams, and enjoy translating complex Statistical Analysis into measurable Business Impact
- You are willing to work on site at our campus 2 days per week
We look forward to receiving your application!