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Jobs in Singapore   »   Jobs in Singapore   »   Transportation / Logistics Job   »   Automotive Engineer
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Automotive Engineer

Lexbuild Motors Pte. Ltd.

Job Description

  • Develop battery data analytics processes and visualizations for vehicle programs.
  • Data management and retrieval using Spark, Hive, Hue, and Jupiter Notebooks.
  • Data analysis using Python, MATLAB, and R.
  • Data visualization with Power BI, Tableau, Matplotlib, and ggplot2.
  • Collaborate with battery data analytics and engineering groups on algorithm design, results, modifications, production issues, data consumption methods, and lessons learned.
  • Apply analytical methods to assemble insight from electric vehicle usage data. Use the appropriate statistical methods to make actionable inferences.
  • Fit comp
  • lex models to multi-factor datasets using Python, MATLAB, R.
  • Model and project the long-term trends of key electric vehicle metrics. Validate results.
  • Apply statistical and machine learning models to understand battery production quality metrics.
  • Contribute to analytics forums and cross-functional groups by sharing learning within and beyond Global Battery Engineering and Automotive Engineering for PSV operation.

Job Requirement

  • Any qualification in Automotive/Electrical/Mechanical Engineering, Computer Science, Applied Mathematics, Statistics, or Data Analytics.
  • Minimum technical knowledge of data analysis methods and success in solving complex problems.
  • Proficiency using relevant tools. (Python, Spark, Hive, MATLAB, Power BI, R)
  • Real-world experience using Hive to query Hadoop data file structures.
  • Practical knowledge of machine learning and predictive methods.
  • Ability to lead multiple projects and assignments with high level of autonomy and accountability for results.
  • Knowledge of high voltage batteries and electrification subsystems.
  • Electrochemistry background.
  • Willingness to learn and quickly adjust to new tools and systems.
  • Capable of converting ambiguous problem statements into concrete project requirements.
  • Proven proficiency in statistical analysis techniques.
  • Practical knowledge of machine learning and predictive methods.

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