Fachbereich Wirtschaftswissenschaften

DATA SCIENCE INTERN WORKING STUDENT FOR SALES BY SAP (F/M/D)

  • Job reference : 393738-42489006
  • Function : Information Systems/Telecom
  • Type of contract : Temporary
  • Localisation : Walldorf 69190, DE
  • Contract duration : Not specified
  • Level of studies : Bachelor's Degree
  • Years of experience : < 6 months

Work with a team of data scientists, data, MLOps and software engineers on ML modeling and deployment of pipelines at all stages of development: data exploration, model training, model fine-tuning and optimization, productive deployment, testing and monitoring. Communicate with stakeholders to understand business processes and model input data. Support a high-visibility project along experienced data scientists and AI developers. Learn about applying data-centric AI development practices. Work with a modern cloud stack (SAP BTP, Hyperscaler offerings)

ROLE REQUIREMENTS

Must have:

  • Bachelor’s Degree in Data Science or related fields,
  • Proficiency in Python and at least one other programming/scripting language (e.g. Java, SQL, Scala),
  • Experienced with basic data science and data visualization packages in Python (e.g., pandas, numpy, seaborn, statsmodels, matplotlib, etc.), working in notebook-based (e.g. Jupyter) or script-based environments,
  • Experience in one or multiple machine learning frameworks (e.g. sklearn, pytorch, tensorflow, keras, MLLib)
  • Knowledgeable on large scale data analysis with spark
  • Good understanding of statistical methods (descriptive analyses, regression modeling, etc.) and model quality assessment (custom metrics, creation of validation sets, etc.) Strong oral and written communication skills in English,
  • General interest in applied machine learning to solve business problems.
  • Experience working with complex tabular data (preprocessing, solving data leakage problems, imbalanced data problems).

 

Nice to have:

  • Experience with explainability and interpretability of machine learning models (SHAP, glass-box models)
  • Experience with Deep Learning architectures (e.g. transformers) Familiar with software version control (e.g. GitHub, Git).
  • Experience with CI/CD frameworks (e.g. Jenkins, Concourse, Gitlab CI/CD)
  • Experience with MLOps tools (e.g., mlflow)
  • Experience in writing tests for ML models.
  • Interest in building model evaluation pipelines.