Expert Data Scientist - Customer & Decision Intelligence (m/f/d) 1

Your Tasks

• Deliver measurable commercial and operational impact through operations intelligence, customer intelligence, and personalization. 


• Contribute to the development of the Decision Science roadmap for operations intelligence and customer intelligence by applying scientifically sound statistical modeling, mathematical optimization, and machine learning. 


• Translate business questions into well-defined mathematical and statistical problems, critically assess the available data, and select and justify the most appropriate modeling approach. 


• Operations Intelligence: develop models for demand forecasting, inventory and replenishment optimization, assortment and allocation, supply chain and logistics optimization, workforce and store capacity planning, and pricing and markdown optimization. 


• Customer Intelligence: develop recommendation systems and models for personalization, customer segmentation, customer lifetime value, churn, propensity, marketing effectiveness, and uplift. 


• Choose methods based on assumptions, interpretability, robustness, computational efficiency, and empirical performance: use a simple linear model when sufficient, and advanced ML or AI only when it adds demonstrable value. 


• Build predictive, prescriptive, and optimization models (e.g., linear/integer programming, simulation, causal inference, experimentation) to improve business performance and operational efficiency. 


• Collaborate with Data Engineers and ML Engineers to build scalable data pipelines, feature stores, and production-ready ML solutions using Google Cloud Platform (BigQuery, Vertex AI). 


• Evaluate, monitor, and continuously improve model performance through baseline comparisons and the validation of assumptions, uncertainty estimates, and generalization, while ensuring business value. 

Your Profile

• Master’s degree (MSc) or PhD from an established, internationally recognized university in Mathematics, Statistics, Physics, Computer Science, Data Science, Operations Research, or a closely related quantitative field. 


• Approximately 4–5 years of relevant professional experience after graduation in data science, statistical modeling, applied mathematics, or machine learning. 


• A strong foundation in probability theory, statistical inference, linear algebra, numerical methods, and mathematical optimization, with the ability to explain the assumptions and limitations of different models. 


• Proven ability to compare classical statistical models, optimization methods, and machine learning approaches and justify the choice using scientific reasoning and evidence. 


• Practical experience in developing and validating predictive and optimization models; experience in operations intelligence (forecasting, inventory, supply chain, and pricing) or customer intelligence (recommendation systems, personalization, and CRM analytics) is an advantage. 


• Experience in e-commerce, marketplaces, digital products, media, retail technology, or customer-facing systems is an advantage. 


• Excellent programming skills in Python and SQL, with experience processing large-scale structured and unstructured datasets. 


• Experience with scientific Python libraries (e.g., NumPy, SciPy, statsmodels, and scikit-learn) and ML frameworks such as XGBoost, LightGBM, TensorFlow, or PyTorch. 


• Familiarity with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and modern MLOps practices, is an advantage. 


• Understanding of modern AI methods, including deep learning and Generative AI / LLMs, and the judgment to identify when these approaches are—or are not—appropriate. 


• Strong analytical and problem-solving skills with the ability to translate business needs into sound mathematical and statistical solutions. 


• Excellent communication and stakeholder management skills, with the ability to explain complex concepts to both technical and business audiences. 


• A collaborative mindset, scientific curiosity, intellectual independence, and a pragmatic approach to delivering measurable business impact. 

About Us

Additional Benefits

Job Infos

​Location: Ingolstadt

MediaMarktSaturn Retail Group

Department: HQ - Priorization Management & CDO

Entrylevel: Professional Level

Type of Employement: Full Time

Working Hours: 37,5

Persona: Job Requisition HQ Employee

Recruiter: Lea Ellerich 

Recruiter: Lea Theresa Ellerich