SAP Intern/ Working Student f/m/d - Data Science 

Germany, Baden-Württemberg 

346559488

THE ROLE

• 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.

Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please also describe your experience and skills in foreign languages and computer programs / programming languages.