The role aims to solve problems related to battery engineering by analyzing factory, user, and failure data, and to improve data accessibility, efficiency, and quality through the development of data models and pipelines.
Requirements
- 2-5 years as data scientist, data engineer or analyst.
- Working knowledge and experience with big data.
- Strong working knowledge of Python, Unix tools, Perl, Github and Tableau.
- Basic knowledge of SQL databases, TCP/IP commands, Minitab, JMP and in bash/Perl environment.
- Candidate must have solid competency in statistics and the ability to provide value-added analysis.
- Familiarity with database modeling and data warehousing principles.
- Experience in designing and building data models to improve accessibility, efficiency, and quality of data.
Responsibilities
- Write Python programs to implement Machine Learning functions and maintain revision in Github.
- Utilize advanced technologies, for modeling enhancements
- Build a high-quality BI and Data Warehousing framework, implementing and operating data pipelines with an understanding of ML lifecycles
- Be able to analyze factory, user, and failure data and use engineering understanding mechanisms to resolve battery problems.
- Deliver high quality analytic insights from a very data warehouse
- Write programs for data filtering, organization, reporting.
- Write programs for uploading to and maintaining data in SQL database.
Other
- Battery Engineering experience desired.
- Self-starter with entrepreneurial experience and ability to interact with other functions in matrix environment.
- Proven creativity to go beyond current tools to deliver best solution to the problem.
- Experience building scalable data pipelines using Spark, Hadoop, etc. preferred
- Desirable for experience with Apple OS, such as iOS, MacOS, etc.
