R&D
Data Analyst
Mobileye is a global pioneer in computer vision, machine learning, data analytics, localization and mapping for ADAS and autonomous driving. Mobileye China R&D Center develops REM, our core mapping & localization solution for autonomous vehicles. We are hiring a Data Analyst to design and deliver robust, high-efficiency validation frameworks for the REM system - a sophisticated ML & image processing pipeline built on million-scale real-world driving datasets, bringing unique technical challenges and growth opportunities. You will design and build data validation infrastructure, tooling and methodologies leveraging state-of-the-art technologies and cloud-native platforms.
What will your job look like:
- Improving quality, efficiency and scale adapation of validation processes for test and product maps built from visual data uploaded by millions of vechicles throughout the world.
- Participate in planning, design and implementation of new validation processes and methodology with technology iteration.
- Define and implement end-to-end validation tools with well designed metircs and insights to reflect map quality.
- Integration of existing data anlysis tools, data pipelines to make robust and scalable end-to-end work flow.
- Build and manage data platforms, including data lakes and data warehouses.
- Management and prioritization of daily tasks.
All you need is:
- BSC/MSc in computer science, mathematics, or other engineering subjects.
- Experience with Python (NumPy, SciPy, Matplotlib, Pandas) for data analysis purpose.
- 3+ years of experience in designing, implementing, and automating data analysis, validation or software testing, with a focus on performance analysis for complex, data-intensive, or machine-learning algorithms.
- Strong analytical capabilities and experience in data processing..
- Ability to juggle multiple tasks and build systematic approach.
- Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
- Fluent English.
Nice to have:
- Knowledge in descriptive statistics, probability, and statistical inference.
- Knowledge in designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
- Knowledge in cloud data environment, such as AWS, including services such as S3, Athena and DynamoDB.


