Thesis - Data Science & Machine Learning in Sales Excellence (d/m/w)

Stellenbeschreibung:

Schaeffler is a dynamic global technology company and its success has been a result of its entrepreneurial spirit and long history of private ownership. Does that sound interesting to you? As a partner to all of the major automobile manufacturers, as well as key players in the aerospace and industrial sectors, we offer you many development opportunities.

General information

Sales Excellence transforms data into clear and actionable insights that enable smarter and more profitable decisions. We develop intelligent tools and harmonized processes that simplify daily work and boost sales performance. By leveraging deep customer insights and building strong technical partnerships, we identify new opportunities that drive sustainable and profitable growth.

A basic requirement for a thesis at Schaeffler is proof of enrollment at the time of the thesis. This position is available from March 1, 2026 for a duration of 3-6 months.

Your Key Responsibilities

Implementation of innovative AI use cases within Sales Excellence, such as machine learning based volume planning and opportunity evaluation
Collection, preprocessing, and normalization of large datasets as a foundation for machine learning models
Development and application of algorithms and tools for data processing and analysis
Validation and performance optimization of machine learning models
Creation of meaningful data analyses and visualizations to support data-driven decision making
Support in the automation of data workflows to increase efficiency
Preparation of technical documentation, reports, and presentations for internal stakeholders

Your Qualifications

Studies in the field of Data Science, Computer Science, Business Informatics or a comparable field
Fluent verbal and written communication skills in English (min. B2 level)
At least basic knowledge of German language
Proficiency in Microsoft Suite, especially in Excel
Strong foundation in machine learning concepts, including supervised learning, classification algorithms, model evaluation and validation techniques
Proficiency in data preprocessing skills such as data cleaning, feature engineering, handling missing values, and normalization
Experience with programming languages and tools commonly used in machine learning, such as Python (libraries like scikit-learn, pandas, numpy, matplotlib)
Understanding of statistical analysis and performance metrics
Skills in data visualization to interpret model results and communicate findings effectively to stakeholders
Familiarity with model deployment and automation concepts is a plus to facilitate integration into business processes
Independent, structured, and responsible working style combined with a strong willingness to learn
Strong teamwork and communication skills

As a global company with employees around the world, it is important to us that we treat each other with respect and value all ideas and perspectives. By appreciating our differences, we inspire creativity and drive innovation. In this way, we contribute to sustainable value creation for our stakeholders and society as a whole. Together, we advance how the world moves.

Exciting assignments and outstanding development opportunities await you because we impact the future with innovation. We look forward to your application.