Expert Data Science (m/f/d)

HSE - Home Shopping Europe GmbH; Ismaning; Vor Ort; EUR 55.000 - 75.000; Vollzeit

Zusammenfassung

HSE - Home Shopping Europe GmbH in Ismaning is seeking a Data Scientist to develop innovative Predictive Models and analyze Customer Behavior. You will work with advanced Machine Learning algorithms in Python and R, optimizing Customer Analytics in a dynamic E-Commerce and TV-Shopping environment.

The ideal candidate has a degree in Data Science or a related field, strong experience in Statistical Analysis, and a passion for translating complex insights into measurable business impact. This role requires fluent English and ideally German, with the option to work on site two days a week.

Qualifikationen

• Strong experience in Statistical Analysis with Python or R.
• Practical expertise in Feature Engineering and Model Evaluation.
• Excellent analytical skills for Customer Intelligence and Retention Analytics.

Aufgaben

• Develop innovative Predictive Models to optimize Customer Journey.
• Implement A/B Testing frameworks and Statistical Modeling.
• Collaborate with Marketing and Product teams for business actions.

Kenntnisse

Predictive Modeling

Customer Behavior Analytics

Statistical Analysis

Python

R

Feature Engineering

Machine Learning

Customer Analytics

Ausbildung

Degree in Data Science, Statistics, or related field

Tools

scikit-learn

pandas

statsmodels

Jobbeschreibung

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!