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.

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 complex 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.

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 complex 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.

Ship Repair Engineer

• Location: Penjuru (Transport provided at Jurong East)
• Monday to Friday: 8:00 AM – 5:00 PM
• Saturday: 8:00 AM – 12:00 PM
• Salary: S$ 3,300 - 4,000

Job scopes:

• Manage day-to-day operations and coordination of afloat repairs, load testing & inspection services on ships in Singapore and the region.
• Assist Service Manager in handling the company’s field service operations, in technical, operational and commercial matters
• Prepare quotations, costing for invoice, tools & equipment lists and procurement of parts.
• Manage and coordinate service job execution.
• Liaise with our customers, such as Ship Managers, Offshore Operators, Shipyards, Agents and others
• Manage the tools & equipment which are kept at our warehouse. Send for recertification periodically as required.
• Coordinate with Ship Agents, Ports & Ship Yards, handle permits and schedule service attendances.
• Coordinate and arrange transport of Engineers, tools & equipment to and from job sites
• Answer customer queries and provide remote technical support.

Job Requirements:

• Diploma in Marine Engineering or similar.
• Past experience in marine cranes & deck machinery required.
• Experience in coordinating marine service work, especially afloat repairs will be an advantage.
• Able to commit overtime.

Apply now for Interview arrangement

Daniel Wong | Senior Consultant | Reg No: R2095781

The Supreme HR Advisory Pte Ltd | EA No: 14C7279