Engineer (18-Month Leased Labor) - Data Analysis and Statistics
On-siteMunchen, Bavaria, Federal Republic of Germany
Job Summary
Conduct scenario data analysis by transforming raw operational data from open and in-house sources into statistically valid evidence linking validation to regulatory frameworks like UN-R157 and the AI Act. Explore and pre- and post-process driving data to implement data processing pipelines, then design and execute statistical analyses using Bayesian inference or Monte Carlo simulations to extrapolate real-world claims. Apply AI methods to data labeling, clustering, and characterization while managing ETL and data quality pipelines. Requires a Master's degree in Statistics or Computer Science with proficiency in Python, R, and frameworks such as pandas and sklearn.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Statistics, Data Analytics, Electrical Engineering or equivalent experience
- Profound knowledge and proficient skills in data analysis and programming languages, e.g., python, R, and frameworks such as pandas, sklearn, scipy and pythorch
- Experience with working with automotive scenario data, e.g., actor trajectory data or simulation in the loop data
- Experience in data preparation pipelines (ETL) and data quality pipelines
- Hands-on attitude and positive engagement to integrate into a high-performance team
- Proficiency in English
- By applying to this position, you agree with our Recruitment Privacy Statement
Desired Qualifications
- Experience in ADAS function development or related automotive functions
- Experience with SQL or no-SQL
- German and/or Chinese knowledge
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