Engineer (18-Month Leased Labor) - Data Analysis and Statistics

In this role you will transform raw automotive data into statistically sound evidence to support safety claims under regulatory frameworks. You will work within Huawei's Automotive Engineering Lab to analyze scenario data, build data pipelines, and apply Bayesian and other statistical methods to extrapolate real-world results. You will also label and cluster data using AI methods and contribute to cross-functional validation efforts. This position offers hands-on data science work in a fast-growing, global engineering team with opportunities for growth and impact.

• healthy meals in company canteen
• training opportunities
• language courses (German and Mandarin)
• diverse, welcoming environment with ~40 nationalities
• self-responsible work in a motivated team

• Analyze scenario data and create rigorous, data-driven evidence for safety claims
• Link data-driven validation to regulatory frameworks (UN-R157, EU Type Approval, AI Act)
• Pre- and post-process driving data from open and in-house sources
• Design and implement data processing pipelines
• Perform statistical analyses (Bayesian inference, Monte Carlo, accelerated testing) to extrapolate real-world data
• Apply AI methods to data labeling, clustering, and characterization

• Bachelor’s or Master’s degree in Computer Science, Statistics, Data Analytics, Electrical Engineering or equivalent experience
• Proficiency in Python and R; experience with pandas, sklearn, scipy; familiarity with PyTorch
• Experience with automotive scenario data (actor trajectory data, simulation-in-the-loop)
• Experience with ETL and data quality pipelines
• English proficiency; German and/or Chinese knowledge is a plus
• Hands-on attitude and ability to integrate into a high-performance team

• Hands-on attitude
• Team collaboration
• Proactive mindset
• Python
• R
• pandas