About the Team and Project
Our current focus is on advancing Proton Exchange Membrane Fuel Cell (PEMFC) power modules, primarily for mobility application.
Based on massive operational data of fuel cell vehicles in field, the work scope include:
- Conduct data mining to harness the accumulated FCEV field data.
- Specific working area includes:
- Uncover hidden insights into fuel cell degradation
- Develop predictive diagnostic functions
- Identify system design optimization opportunities
- Train advanced AI models.
- Work closely with corporate research hub in Renningen, Germany, on project activities and competence development.
- Work closely with business units to supply cutting edge and competitive technology solutions and to transform them to products.
- Execute technology scouting in China/Asia covering both academia and industry for preparing strategic decisions.
We are seeking a highly motivated and innovative Data Scientist to lead the data analysis efforts for this critical initiative.
Key Responsibilities
- Data Processing & Visualization: Clean, process, and analyze massive volumes of time-series field data.
- Independent Data Exploration: Proactively explore the data with an innovative mindset to discover valuable insights regarding fuel cell degradation behaviors and influencing environmental/operational factors.
- Advanced AI & Machine Learning: Design, train, and deploy machine learning models to solve complex engineering challenges.
- Design Optimization Support: Identify potential design flaws or operational inefficiencies through data forensics and provide actionable feedback to support continuous hardware and software design iterations.
- Cross-Functional Collaboration: Act as the bridge between data science and physical engineering. Work closely with fuel cell domain experts to contextualize data findings and translate them into real-world system improvements.
- Cloud Database Management: Manage the project's data on Cloud, ensuring efficient data retrieval and pipeline operations using HBase, Redis, Kafka, Spark, and MySQL.