Lesson Learned Jobs

Vehicle Synthesis Responsible / PROJECT RESPONSIBLE (PR)

RLE India Private Limited•

Pune

•full time

Job Summary We are seeking a highly motivated and experienced Vehicle Synthesis Responsible / PROJECT RESPONSIBLE (PR) to join our team within the Automotive industry. This role requires an onsite presence and will be pivotal in ensuring the successful synthesis and management of vehicle projects. Key Responsibilities The Vehicle Synthesis Responsible / PROJECT RESPONSIBLE (PR) will be responsible for overseeing and coordinating the synthesis of vehicle components and systems, ensuring alignment with project goals, quality standards, and cost targets. This includes managing the implementation of design changes, analyzing weight deviations, and incorporating lessons learned to continuously improve processes and outcomes. Required Skills & Qualifications Architecture: Demonstrated ability to understand and apply vehicle architecture principles to ensure cohesive system integration and optimal performance. Quality: A strong commitment to quality assurance and a proven track record of implementing quality control measures throughout the vehicle synthesis process. Cost: Experience in managing project costs effectively, identifying cost-saving opportunities, and ensuring adherence to budgetary constraints. Technical: Possessing a strong technical understanding of vehicle systems and components, enabling effective problem-solving and decision-making. Performance: Ability to analyze vehicle performance metrics and identify areas for improvement through design optimization and system integration. Standardization: Experience in developing and implementing standardization processes to ensure consistency and efficiency in vehicle synthesis. Innovation: A proactive approach to identifying and implementing innovative solutions to enhance vehicle design and performance. Benchmark: Ability to conduct benchmark studies and analyze competitor vehicles to identify best practices and areas for improvement. Timing: Excellent time management and organizational skills, with the ability to prioritize tasks and meet deadlines effectively. Design Changes: Experience in managing and implementing design changes, ensuring minimal disruption to project timelines and quality standards. Weight Deviations: Ability to analyze and address weight deviations, identifying root causes and implementing corrective actions. Lesson Learned: A commitment to documenting and sharing lessons learned to continuously improve processes and prevent future errors. Internal Control System: Familiarity with and adherence to internal control systems to ensure compliance and accountability. Experience Required: The ideal candidate will possess a minimum of 6 to 9 years of relevant experience in vehicle synthesis or a related field. This level of experience indicates a high degree of proficiency and the ability to lead and manage complex projects effectively. What We Offer Salary: (No salary information provided)

Quality Data Analyst – Electrical Hardware Engineering, Warranty Analytics | KPI Automation | Design Assessment | AI Adoption

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our team. This role will focus on leveraging data analysis and advanced techniques to support our Electrical Hardware Engineering, Warranty Analytics, KPI Automation, Design Assessment, and AI Adoption initiatives within the Automotive / Technology industry. The ideal candidate will possess a strong analytical background and a passion for driving data-driven decisions. Key Responsibilities This role will be responsible for a range of tasks including data analysis, visualization, and reporting to support quality initiatives. The candidate will be expected to identify trends, anomalies, and opportunities for improvement within warranty data, cost trends, and design performance. They will also be involved in the automation of KPI reporting and the implementation of AI -assisted analytics to enhance predictive quality and drive corrective action management . Required Skills & Qualifications Data Analysis: Demonstrated ability to extract, clean, and analyze large datasets to identify meaningful insights and trends. Data Visualization: Proficiency in creating compelling and informative data visualizations using tools such as Power BI and Excel Analytics to communicate complex information effectively. Dashboarding & KPI Reporting: Experience in designing and developing interactive dashboards and automated KPI reports to track key performance indicators and monitor quality metrics. Data Storytelling: Ability to translate data insights into clear and concise narratives that resonate with stakeholders and drive informed decision-making. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis, scripting, and automation. Databricks: Familiarity with Databricks for data processing and analytics. Power Automate: Experience with Power Automate for workflow automation and data integration. Warranty Data Analytics: Expertise in analyzing warranty data to identify root causes of failures, predict future trends, and optimize product designs. Cost Trend Analysis: Ability to analyze cost trends to identify areas for cost reduction and process improvement. KPI Automation: Experience in automating KPI reporting and data collection processes. Multi-Source Data Integration: Ability to integrate data from multiple sources to create a comprehensive view of quality performance. AI-Assisted Analytics: Experience leveraging AI and Generative AI techniques to enhance data analysis and predictive modeling. Predictive Quality: Ability to apply statistical methods and machine learning algorithms to predict product quality and identify potential issues proactively. Anomaly Detection: Experience in identifying and investigating anomalies in data to uncover potential quality problems. Root Cause Analysis: Expertise in conducting root cause analysis to identify the underlying causes of quality issues. Corrective Action Management: Ability to develop and implement corrective action plans to address quality issues and prevent recurrence. DFMEA, DRBFM, APQP: Familiarity with DFMEA , DRBFM , and APQP methodologies for design and process improvement. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality control. Structured Problem Solving: Ability to apply structured problem-solving techniques to identify and resolve quality issues. Process Optimization: Experience in identifying and implementing process optimization initiatives to improve quality and efficiency. Lean & Six Sigma: Knowledge of Lean and Six Sigma principles for continuous improvement. Quality Tools: Familiarity with various quality tools and techniques for data analysis and problem-solving. Issue Management: Ability to effectively manage and track quality issues to resolution. Warranty Management: Experience in managing warranty claims and analyzing warranty data. Field Quality Analysis: Ability to analyze field quality data to identify trends and patterns. Design Assessment: Ability to conduct design assessments to identify potential quality risks and improve product designs. Design Integrity: Understanding of design integrity principles and their impact on product quality. Design Robustness: Ability to evaluate and improve the design robustness of products. Lessons Learned Deployment: Ability to capture and deploy lessons learned from quality issues to prevent recurrence. Analytical Skills: Strong analytical skills with the ability to interpret data and draw meaningful conclusions. Problem-Solving Skills: Excellent problem-solving skills with the ability to identify and resolve complex quality issues. Data Interpretation Skills: Ability to accurately interpret data and translate it into actionable insights. Communication Skills: Excellent communication skills with the ability to effectively communicate technical information to both technical and non-technical audiences. Stakeholder Management: Ability to build and maintain relationships with key stakeholders . Leadership-Ready Presentation Skills: Ability to deliver compelling and persuasive presentations to senior management. Qualifications: Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. What We Offer Experience Required: 5 - 10 years of relevant experience. Salary:

Virtual Analysis Engineer L2 Safety

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and motivated Virtual Analysis Engineer L2 Safety to join our team. This is a remote position within the Automobile industry. The ideal candidate will possess a strong analytical background and experience in performing virtual analysis to ensure the safety and performance of our vehicles. Key Responsibilities The Virtual Analysis Engineer L2 Safety will be responsible for conducting comprehensive CAE analysis , contributing to design reviews , and identifying opportunities for structural improvements . This role requires a proactive approach to problem-solving, clear communication of findings and lessons learned , and a commitment to teamwork . Regular project updates will be essential, ensuring stakeholders are informed of progress and any potential challenges. Required Skills & Qualifications Education: A B.E , B.Tech (Mechanical, Automobile), M.E , or M.Tech degree is required. Experience: 3 - 7 years of experience in a related field is expected, demonstrating a solid foundation in virtual analysis and a proven ability to contribute effectively to a team. CAE Analysis: Proficiency in performing CAE analysis , including Occupant simulations and analysis at both Vehicle level and Sled level . Model Refinement & Quality Assessment: Experience in model refinement and rigorous quality assessment of simulation results. Analytical & Problem-Solving Skills: Demonstrated analytical skills and problem-solving skills , with the ability to identify root causes and propose effective solutions. Engineering Fundamentals: A strong understanding of Classical Mechanics , Applied Mechanics , Strength of Materials , and Physics fundamentals . Human Body Modeling: Experience with Human Body Model (HBM) simulations. Scripting & AI Tools: Familiarity with scripting and the application of AI tools in the analysis process. Materials Expertise: Knowledge of Metals and Composite parts , including failure analysis techniques. Cross-Functional Collaboration: Ability to effectively collaborate with cross functional performance requirements teams. Design & Presentation: Ability to contribute to design proposals and deliver clear and concise presentations . Professional Attributes: Demonstrated responsibility , ownership , and a strong learning aptitude . Communication Skills: Excellent communication skills , both written and verbal. Logical Reasoning: Strong logical reasoning abilities. What We Offer Salary: