Data Scientist, MILES

• This role is ideal for someone with a strong technical foundation and a high sense of ownership, taking projects from idea to execution
• You are open-minded to learn new techniques and tools and feel comfortable with a steep learning curve
• Education: You hold a Master’s degree in a relevant field such as Data Science, Computer Science, Engineering, Statistics or a related discipline
• Experience: You have already gained first work experience as an intern, working student or full-time and had direct contact with real-world ML projects and applications
• Profile: You want to make an impact by not just building models but also creating solutions that last. You're energized by turning raw data into valuable products, and you're not afraid to explore, test, fail, and improve. You have a general interest in Artificial Intelligence applications and their strategic impact on business decisions within the mobility sector
• Proficient in Python and relevant ML libraries: scikit-learn, TensorFlow, Keras
• Good Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, cross-validation
• Good SQL knowledge for data extraction and manipulation
• Familiarity with computer vision and image analysis
• AI Exposure: Strong interest in AI technologies and their practical application in business processes. Previous experience with AI tools is a plus
• Languages: Excellent communication skills in English (both written and verbal). Proficiency in German is a significant advantage

Desirable

• As a Data Scientist at MILES, you’ll go beyond model development to create end-to-end data science solutions that influence business decisions, product features, and internal tooling
• Data Preparation and Analysis
• Take responsibility for preparing datasets, exploring data quality issues, and conducting exploratory analyses. Proactively identify patterns and insights to support modeling and decision-making efforts
• Independently Drive Subsections of Projects
• Manage well-defined workstreams within larger projects, such as building preprocessing pipelines, designing experiments, or maintaining monitoring dashboards,with increasing autonomy and accountability over time
• Support Model Development and Evaluation
• Contribute to the development and validation of machine learning models, including feature engineering, training, and performance tracking. Collaborate with our Senior Data Scientist on improving model quality and scalability
• Maintain Clear Communication and Documentation
• Document technical decisions, results, and workflows clearly and systematically. Communicate progress effectively with the team and stakeholders, and be prepared to present findings or contribute to discussions when needed