About the job
Embark on a transformative journey with Kia Europe!

We are thrilled to announce an exciting internship opportunity for an Intern Data Scientist at our Kia Europe Headquarters located in Frankfurt/Main, Germany.
What We Are Looking For:
As a prerequisite for this internship, candidates must be enrolled in a university within the European Union throughout the internship period. Additionally, a valid visa and an unrestricted work permit in Germany are essential. We recommend a six-month internship duration to facilitate a comprehensive learning experience at Kia Europe.
Your Role:
In the role of an Intern Data Scientist, you will play a crucial part in enhancing Ownership Experience Business Intelligence and Data Integration tools. Your contributions will significantly improve the department's data visibility and forecasting capabilities by providing actionable insights that drive better business outcomes.
Main Responsibilities:
Extract and integrate data from various systems, including ERP, SQL databases, and SAP.
Develop comprehensive reports and analyses for Ownership Experience Teams (BI, Warranty, Technical Support, Parts & Accessories, Service Marketing, OX Academy).
Define, implement, and maintain KPIs for Ownership Experience Teams.
Ensure successful maintenance and reporting of the KPIs database.
Process and visualize data using tools such as Tableau and Python libraries (Numpy, Pandas, Matplotlib, Seaborn).
Gain a thorough understanding of the Kia EU Ownership Experience Data Structure.
Support Kia EU Ownership Experience Teams in ongoing data interfacing projects.
Prepare pre-decision materials based on data analysis for the Kia EU Ownership Experience when required.
Assist in the development and enhancement of a new warranty reporting portal to track and manage market KPIs.
Your Qualifications:
Education:
Currently pursuing a Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, Business Science, or a related field.
Proficiency in Python scripting and SQL.
Familiarity with data analysis packages or databases, such as SQL, SAS, R, SPSS, Python, and VBA.
