Assignment Description

Our client in the automotive industry is currently seeking a Senior Data Scientist with excellent software development skills. In this role, you will assist our client in developing data science products that uncover valuable insights from vast amounts of data, helping them make smarter decisions to deliver superior vehicles and enhance the overall product experience. Your primary focus will be on developing world-class data analytics and AI products by applying scientifically established methods such as statistics, machine learning, and deep learning. Additionally, you may have the opportunity to contribute to the development of novel data science methods, particularly in the area of automotive safety.

At our client’s Safety Centre, 200 highly skilled professionals strive every day to make the world a safer place for vehicle occupants, our loved ones, and those around them. Covering both Safety and Durability attributes, they courageously lead the way in supporting the company’s strategic direction: Freedom to move in a personal, sustainable, and safe manner.

The Data, Analytics, and Artificial Intelligence team currently works with real-world safety data, understanding accident causation mechanisms, and laying the foundations for future safety features and functions in upcoming car development programs. They contribute their expertise to car programs through data analysis, providing the knowledge necessary to drive the engineering of world-leading products. This work is conducted in close collaboration with our client’s digital organization, which provides the digital infrastructure for storing and analyzing real-world data.

Main Responsibilities:

• Map business questions into an analytical context, outlining the choice of methods and analytical subsets of data.
• Pre-process structured and unstructured data, including cleansing and validating the quality and integrity of data in the analytical context.
• Enhance data collection procedures to include all relevant information for developing analytic products, with the ability to fuse multiple datasets in a given context.
• Implement appropriate statistical, machine learning, and/or deep learning methods for relevant business questions and datasets.
• Develop and deploy data science products in cloud or on-premise infrastructure.
• Communicate and collaborate with other departments, ensuring best practices are followed in designing and documenting solutions.

Required Qualifications:

• University degree in a quantitative discipline (e.g., Mathematics, Computer Science, Data Science, Natural Sciences, etc.) or equivalent work experience.
• Proficiency in writing high-quality data science code in Python, with a proven track record and knowledge of best practices and coding standards. Familiarity with Python-based data processing and analysis libraries.
• Experience in visualizing insights using dashboards or similar solutions, either off-the-shelf or Python-based frameworks.
• Experience in developing Python-based dashboards using Streamlit, Plotly Dash, or similar tools.
• Experience in developing applied generative AI applications and related solutions.
• Significant experience in developing end-to-end data science software solutions.
• Expertise in state-of-the-art data science and machine learning practices, along with advanced knowledge of Python-based ML and DL libraries, and version control (e.g., Git and GitHub).
• Experience in developing scalable ML-based production systems in the cloud, using platforms such as Databricks and Azure.
• Independent working style with a self-confident appearance, including at the management level.
• Fluency in English (written and verbal).

Meritorious Competences:

• Work experience with vehicle safety data and principles.
• Familiarity with ML-ops and cloud environments.
• Proven experience with Kubernetes and Docker.
• Knowledge of and interest in data engineering aspects and data pipelines.
• Ability to code in R and/or MATLAB.

Desired Attributes:

• Passion for data science and analysis.
• Structured approach to work and strong documentation skills.
• Self-driven and result-oriented team player.
• Willingness to learn and improve.