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

- **Company:** Huawei's Heisenberg Research Center
- **Location:** München, Germany
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Data Analysis, Data Cleansing, Extract Transform Load (ETL), Python (Programming Language), Monte Carlo Methods, Operational Data Store, SciPy, SQL Databases, Pandas, Scikit Learn, Information Technology, Data Analytics, Data Pipelines, Programming Languages
- **Published:** July 23, 2026
- **Apply:** https://www.careerjet.de/jobad/de92373c81bc8b49fc04e72a0e3f981a97

## About the Role

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.
Experience in ADAS function development or related automotive functions is an advantage.
Experience with SQL or no-SQL is an advantage.
Hands-on attitude and positive engagement to integrate into a high-performance team.
Proficiency in English. German and/or Chinese knowledge are an advantage.

## Description

Huawei's Heisenberg Research Center in Munich is responsible for advanced technology research, architectural development, design and strategic engineering of our products.
In the Automotive Engineering Lab (AEL) teams are rapidly growing and focused on advanced automotive technologies in multiple domains.
Join Automotive Engineering Lab (AEL) as:
Engineer (18-Month Leased Labor) - Data Analysis and Statistics (m/f/d)
Your mission
Conduct scenario data analysis, transforming raw operational data from open and in-house sources into rigorous, statistically valid data-driven evidence. Link between data-driven validation and regulatory frameworks such as UN-R157, EU Type Approval, and the AI Act, focused on supporting safety claims by robust statistical methods.
Explore and pre- and post-process driving data from open data and in-house data sources. Implementing data processing pipelines.
Design and execute statistical data analysis (e.g., using Bayesian inference, Monte Carlo simulations, or accelerated testing methods) to extrapolate real-world data into statistically significant claims.
Apply AI methods to data labeling, clustering, characterization.
Your areas of expertise


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