Data Analysis Jobs in Chennai

Quality Data Analyst – Electrical Hardware EngineeringWarranty 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 Electrical Hardware Engineering team. This role will focus on Warranty Analytics, KPI Automation, Design Assessment, and the adoption of AI within our quality processes. The ideal candidate will possess a strong analytical background and a passion for leveraging data to drive improvements in product quality and operational efficiency. This is an onsite position. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks including: Performing Data Analysis to identify trends and patterns in warranty data, product performance, and manufacturing processes. Developing and maintaining KPI Reporting dashboards to track key quality metrics and provide actionable insights to stakeholders. Automating KPI generation and reporting processes to improve efficiency and accuracy. Conducting Root-Cause Analysis of quality issues and collaborating with engineering teams to implement effective Corrective Action Management plans. Utilizing Data Mining techniques to uncover hidden patterns and insights within large datasets. Applying Statistical Analysis methods to evaluate product performance and identify areas for improvement. Leveraging AI-Assisted Analytics and Generative AI to enhance data analysis capabilities and identify potential quality risks. Implementing Process Optimization strategies to streamline quality control processes and improve overall efficiency. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. 5-10 years of experience in a data analysis role, preferably within the automotive or technology industry. This level of experience indicates a proven ability to independently manage complex data analysis projects and deliver impactful insights. Data Analysis : A strong foundation in data analysis techniques, including data cleaning, transformation, and exploration. Data Visualization : Proficiency in creating compelling and informative data visualizations to communicate insights effectively. Dashboarding : Experience in designing and developing interactive dashboards using tools such as Power BI . KPI Reporting : Ability to define, track, and report on key performance indicators ( KPIs ) to measure quality performance. Data Storytelling : Skill in translating complex data into clear and concise narratives that resonate with stakeholders. Quality Tools : Familiarity with various quality tools and methodologies, such as Lean and Six Sigma . Issue Management : Experience in identifying, tracking, and resolving quality issues in a timely and effective manner. Root-Cause Analysis : Ability to conduct thorough root-cause analyses to identify the underlying causes of quality problems. Corrective Action Management : Experience in developing and implementing corrective action plans to prevent recurrence of quality issues. Process Optimization : Ability to identify and implement process improvements to enhance quality control processes. Power BI : Proficiency in using Power BI to create interactive dashboards and reports. Excel Analytics : Advanced skills in Excel for data analysis and reporting. SQL : Strong proficiency in SQL for querying and manipulating data. Python : Experience using Python for data analysis and automation. Databricks : Familiarity with Databricks for big data processing and analysis. Power Automate : Experience using Power Automate for automating data-related tasks. Warranty Data Analytics : Experience analyzing warranty data to identify trends and patterns. Cost Trend Analysis : Ability to analyze cost trends to identify opportunities for cost savings. KPI Automation : Experience automating KPI generation and reporting processes. Multi-Source Data Integration : Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics : Experience leveraging AI to enhance data analysis capabilities. Predictive Quality : Ability to use data to predict potential quality issues. Anomaly Detection : Skill in identifying unusual patterns or outliers in data. Generative AI : Familiarity with Generative AI techniques for data analysis and insights. Process Automation : Experience automating manual processes to improve efficiency. Data Mining : Ability to extract valuable insights from large datasets. Statistical Analysis : Proficiency in applying statistical methods to analyze data. Quality Metrics : Understanding of key quality metrics and their application. Data Definitions : Ability to define clear and consistent data definitions. What We Offer We offer a competitive salary of .

Quality Data Analyst – Electrical Hardware Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our Electrical Hardware Engineering, Warranty Analytics & Quality Automation team. This role will be instrumental in leveraging data to drive quality improvements, identify trends, and ensure the reliability of our products. The ideal candidate will possess a strong analytical background, a passion for data-driven decision-making, and a commitment to continuous improvement within the automotive and technology industries. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks related to data analysis, reporting, and process improvement. This includes conducting in-depth analysis of warranty data, identifying cost trends, and developing automated reporting solutions. The role will also involve collaborating with cross-functional teams to implement corrective actions and preventative measures to enhance product quality and reliability. Required Skills & Qualifications To be successful in this role, candidates must possess a combination of technical skills, analytical abilities, and a strong understanding of quality methodologies. Specific requirements include: Analytical Skills: Demonstrated ability to analyze complex data sets, identify patterns, and draw meaningful conclusions. Problem-Solving Skills: Proven ability to approach complex problems systematically, identify root causes, and develop effective solutions. Data Analysis: Proficiency in data analysis techniques, including statistical analysis and data mining. Data Visualization: Ability to create clear and compelling data visualizations to communicate insights effectively. Dashboarding: Experience in designing and developing interactive dashboards to monitor key performance indicators (KPIs). KPI Reporting: Ability to generate regular reports on KPIs and present findings to stakeholders. Data Storytelling: Ability to translate data into a narrative that is easy to understand and actionable. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis and automation. Databricks: Familiarity with Databricks for large-scale data processing and analytics. Power Automate: Experience with Power Automate for automating data-related tasks and workflows. Warranty Data Analytics: Expertise in analyzing warranty data to identify trends and opportunities for improvement. Cost Trend Analysis: Ability to analyze cost data to identify trends and potential cost savings. KPI Automation: Experience in automating the generation and distribution of KPIs. Multi-Source Data Integration: Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics: Experience leveraging AI to enhance data analysis and predictive modeling. Predictive Quality: Knowledge of predictive quality techniques to anticipate and prevent quality issues. Anomaly Detection: Ability to identify unusual patterns or outliers in data that may indicate quality problems. Generative AI: Familiarity with Generative AI techniques for data analysis and problem-solving. Issue Management: Experience in tracking and resolving quality issues. Root-Cause Analysis: Proficiency in conducting root-cause analysis to identify the underlying causes of quality problems. Corrective Action Management: Ability to develop and implement effective corrective actions to prevent recurrence of quality issues. DFMEA: Understanding of DFMEA (Design Failure Mode and Effects Analysis) principles. DRBFM: Understanding of DRBFM (Design Review Based on Failure Mode) principles. APQP: Understanding of APQP (Advanced Product Quality Planning) principles. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality improvement. Structured Problem Solving: Ability to apply structured problem-solving methodologies to address quality challenges. Power BI: Proficiency in Power BI for data visualization and reporting. Excel Analytics: Strong Excel skills for data analysis and reporting. Process Optimization: Ability to identify and implement process improvements to enhance quality and efficiency. Six Sigma: Knowledge of Six Sigma methodologies for process improvement. Quality Tools: Familiarity with various quality tools and techniques. Lean: Understanding of Lean principles for waste reduction and process improvement. Education: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline is required. Experience: The ideal candidate will have 5-10 years of experience in a related field, demonstrating a strong track record of success in data analysis and quality improvement. This level of experience is expected to provide a solid foundation for independent work and leadership within a team. What We Offer Salary:

CAE Analyst

RLE India Private Limited•

Chennai

•Full-time

CAE Analyst Job Description Job Summary We are seeking a skilled and motivated CAE Analyst to join our team in Chennai. This role will focus on performing comprehensive analyses to support the development and validation of automotive components and systems. The ideal candidate will possess a strong understanding of computational fluid dynamics, heat transfer, and structural analysis principles, along with proficiency in industry-standard CAE software. Key Responsibilities The CAE Analyst will be responsible for the following: Performing CFD , Heat Transfer , and Full Vehicle Analysis to evaluate the performance and durability of automotive components. Developing and executing CAE simulation models using ANSA , STAR CCM+ , ENSIGHT , and UH3D . Conducting Heat Exchanger analysis and generating Heat Exchanger Data Sheet . Performing FAN Modeling . Collaborating with engineering teams to interpret simulation results and provide design recommendations. Validating simulation results against experimental data and identifying areas for improvement. Creating and maintaining CAE simulation workflows and best practices. Required Skills & Qualifications To be considered for this position, candidates must possess the following: B.E / B.Tech / M.E / M.Tech degree in Mechanical Engineering or a related field. 3 - 6 years of experience in performing CAE analysis within the automotive industry. This level of experience indicates a proficiency in independently executing analyses, interpreting results, and contributing to design improvements. Proficiency in ANSA for mesh generation and pre-processing. Strong experience with RADTHERM/TAITHERM for thermal analysis. Expertise in STAR CCM+ for CFD simulations. Experience with ENSIGHT for post-processing and visualization of simulation results. Familiarity with Team Center for data management and collaboration. Solid understanding of Heat Transfer principles, including conduction, convection, and radiation. Strong foundation in Fluid Dynamics principles, including laminar and turbulent flow. Ability to effectively communicate technical findings and recommendations, both verbally and in written reports. Demonstrated ability to work effectively as a Team Player within a collaborative engineering environment. What We Offer Salary: 90 LPA - 105 LPA

CAE Analyst

RLE India Private Limited•

Chennai

•Full-time

CAE Analyst Job Description Job Summary We are seeking a skilled and experienced CAE Analyst to join our team in Chennai. This role is crucial for supporting our Automotive / Mechanical Engineering initiatives, ensuring the quality and durability of our components and systems. Key Responsibilities The CAE Analyst will be responsible for performing a wide range of CAE simulations and analyses to support product development and validation. This includes, but is not limited to, conducting structural analysis , stress analysis , and fatigue life prediction . The role will also involve root cause analysis and failure analysis to identify and resolve potential issues. The analyst will work closely with design and validation teams to ensure that designs meet performance and durability requirements. Required Skills & Qualifications The ideal candidate will possess a strong foundation in Mechanical Engineering and a proven ability to apply CAE principles to solve real-world engineering problems. A B.E / B.Tech / M.E / M.Tech degree is required. Non-linear FE analysis: Proficiency in performing advanced finite element analyses, including non-linear simulations to accurately predict component behavior under complex loading conditions. Abaqus: Demonstrated experience using Abaqus for conducting FE simulations. FE model building: Ability to create accurate and efficient FE models representing complex geometries and boundary conditions. Meshing: Expertise in generating high-quality meshes using industry-standard tools. HyperMesh: Experience utilizing HyperMesh for efficient mesh generation and model preparation. ANSA: Familiarity with ANSA for pre- and post-processing of FE models. Fatigue life prediction: Ability to perform fatigue life prediction using established methodologies and software. FEMFAT: Experience with FEMFAT for fatigue analysis and damage assessment. Structural analysis: A strong understanding of structural analysis principles and their application to automotive components. Stress analysis: Ability to perform detailed stress analysis to identify areas of high stress concentration and potential failure. Material modeling: Knowledge of material modeling techniques and their impact on simulation results. Contact definitions: Ability to accurately define and implement contact definitions in FE models. Reliability assessments: Experience in performing reliability assessments to evaluate the long-term performance of components. Durability assessments: Ability to conduct durability assessments to ensure components can withstand expected usage conditions. Root cause analysis: Proven ability to perform root cause analysis to identify the underlying causes of failures. Failure analysis: Experience in conducting failure analysis to determine the mechanisms of failure. Automotive engineering: A solid understanding of Automotive engineering principles and practices. Quality processes: Familiarity with quality processes and their application to product development. Robust design methodologies: Knowledge of robust design methodologies to create designs that are insensitive to variations in manufacturing and operating conditions. Manufacturing best practices: Understanding of manufacturing best practices and their impact on component performance. Transmission & driveline systems: Familiarity with Transmission & driveline systems and their components. Gears, Shafts, Clutches, Differentials, Propshafts, Half-shafts, Bearings: Knowledge of the design and analysis of these key components. HyperWorks: Experience with HyperWorks for CAE simulation and analysis. Fatigue life/Damage assessment: Ability to perform fatigue life/Damage assessment to predict component lifespan. Boundary conditions: Ability to accurately define and apply appropriate boundary conditions in FE models. Dynamic loading scenarios: Experience in simulating dynamic loading scenarios to evaluate component response to transient loads. Gear strength: Ability to assess gear strength and durability. Shaft durability: Ability to assess shaft durability under various loading conditions. Road load data: Experience in utilizing road load data for simulation. Simulation load cases: Ability to develop and apply appropriate simulation load cases . Physical test data: Ability to correlate simulation results with physical test data . Refine models: Ability to refine models based on simulation results and experimental data. Material properties: Understanding of material properties and their impact on simulation results. Manufacturing processes: Familiarity with manufacturing processes such as Forging, Casting, and Heat treatment . Component durability: Ability to assess component durability under various operating conditions. CAE simulation tools: Proficiency in using various CAE simulation tools . Customer usage profiles: Ability to incorporate customer usage profiles into simulation models. Duty cycles: Ability to define and apply appropriate duty cycles in simulations. Design robustness: Ability to assess and improve design robustness . DFMEA: Familiarity with DFMEA (Design Failure Mode and Effects Analysis). DVP&R: Understanding of DVP&R (Design Verification Plan and Release). Experience Required: The role requires 4 - 9 years of relevant experience in CAE analysis, preferably within the Automotive or Mechanical Engineering industry. Candidates with a strong track record of solving complex engineering problems and delivering high-quality results are highly encouraged to apply. What We Offer Salary: ₹10 LPA - ₹12 LPA

Software Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and motivated Software Engineer to join our dynamic team. This is an onsite position within the IT / Technology industry. Key Responsibilities This role will involve a range of responsibilities related to software development and maintenance, leveraging a full stack skillset to contribute to our engineering design and manufacturing processes. Required Skills & Qualifications Teamcenter Development: Demonstrated proficiency in developing and maintaining applications within the Teamcenter environment. Java: Strong understanding and practical experience with Java programming language. Full Stack Development: Ability to work across the entire software development lifecycle, from front-end to back-end. GCP: Familiarity with Google Cloud Platform (GCP) for cloud-based solutions. ITK: Experience with ITK (Integration Toolkit) for seamless integration of systems. SOA: Solid understanding of Service Oriented Architecture (SOA) principles and implementation. BMIDE: Experience with Business Modeler IDE for efficient business process modeling. Business Modeler IDE: Ability to utilize Business Modeler IDE to design and implement business processes. XRT: Knowledge of XRT related functionalities. Engineering Design: Understanding of Engineering Design principles and their application in software development. Manufacturing: Knowledge of Manufacturing processes and their integration with software systems. Active Workspace: Experience with Active Workspace for user interaction and data management. Data Models: Ability to design and implement robust Data Models . Business Objects: Experience working with Business Objects and their manipulation. Attributes: Understanding of Attributes and their role in data management. GRM Rules: Ability to configure and manage GRM (Group Rules Management) rules. LOVs: Experience with LOVs (Lists of Values) and their implementation. Declarative UI Components: Ability to develop and utilize Declarative UI Components for user interfaces. Root Cause Analysis: Strong analytical skills with the ability to perform Root Cause Analysis to identify and resolve issues. Database Queries: Proficiency in writing and executing Database Queries for data retrieval and manipulation. PLM Best Practices: Knowledge of PLM (Product Lifecycle Management) Best Practices . Integration Toolkit: Experience with Integration Toolkit for system integration. Web Services: Understanding of Web Services and their implementation. Qualifications: A Bachelor's Degree is required. Experience Required: 4 - 5 years of relevant experience are expected, demonstrating a solid foundation in software engineering principles and practices. This level of experience indicates a readiness to contribute independently and collaboratively within a team. What We Offer Salary: 15 LPA - 16 LPA

Energy Management -Vehicle performance test engineer

RLE India Private Limited•

Pune

•full time

JOB DESCRIPTION Position Title: Vehicle Performance Test Engineer Job Posting Category: Product Design & Engineering - Engineering Job Description The Test Engineer is responsible for passenger vehicle testing per the DVP plan and for providing test results for comparison against vehicle targets. These tasks are needed throughout all the development stages of a vehicle project, from the Mule stage to the final production. Vehicle testing must be performed on standard tracks at test sites equipped with the required instrumentation and test data analysis software. Typical activities include: (Preferably in passenger car) Perform DVP tests – Vehicle Coast Down, Full & part performance, on-road fuel economy, Gradeability, Max speed, Emission testing (TA & COP), etc. Perform subjective assessments for vehicle drivability, performance & Gear shift quality for manual and automatic transmission applications. Perform test data analysis and reports with observations. Perform benchmark vehicle testing and support for data comparison Perform diagnosis and root cause analysis for issues observed with the car Interaction with the Benchmarking team and Program team for data seeking and technical discussions Interaction with calibrators – application managers – chief engineers – site lead for discussion of results and possible requests of clarification Experience in using testing tools/instruments like V Box, Ipetronic, L350 Aqua sensor, CAN analyser, DFL. Experience in using INCA/ETAS/MDA for Data logging during testing Educational /Technical/Experience Basic Qualifications: (In passenger car segment) Bachelor’s degree in mechanical or Automobile Engineering 6 to 8 years of vehicle Energy management performance testing preferable for passenger cars Proficiency in actual vehicle testing at standard tracks (VRDE, NATRAX etc) Previous job in a vehicle testing department & hands-on experience with related instrumentation devices Experience/competence in data analysis with Excel, MDA, Power BI etc. Strong proficiency in Office suites (Google Slides, Google Sheets, Excel, PowerPoint etc) Soft skills : ● Ability to create concise and detailed technical reports. ● Good teamwork capability (communication and data sharing-review with peers) ● Capability to connect autonomously with the rest of the company as needed

Thermal performance Engineer

RLE India Private Limited•

Pune

•full time

Job Summary SENIOR EXECUTIVE - TARLE TECHNOLOGIES PRIVATE LIMITED is seeking a highly motivated and experienced professional to join our team. This role is within the Automotive industry and requires a strong background in mechanical or automotive engineering principles. We are looking for a candidate with a proven track record of success in managing and executing complex engineering projects. Key Responsibilities The Senior Executive will be responsible for overseeing and contributing to various aspects of project performance engineering, ensuring the successful delivery of projects within the Automotive domain. This includes coordinating efforts across multiple functional teams and providing regular reporting on project status and performance. Required Skills & Qualifications Education: A Bachelor’s or Master’s degree in the Mechanical or Automotive domain is required. Experience: A minimum of 8-12 years of relevant experience is expected. This seniority level requires a candidate capable of independent project management, mentoring junior engineers, and contributing to strategic decision-making. Project Performance Engineering: Demonstrated ability to analyze and improve project performance, identifying and implementing strategies to optimize efficiency and effectiveness. Functional Synthesis: Proficiency in synthesizing information from various functional areas to create a cohesive and integrated approach to problem-solving. Cross-Functional Coordination: Excellent ability to facilitate collaboration and communication across different teams and departments, ensuring alignment and shared goals. Validation Planning: Experience in developing and executing comprehensive validation plans to ensure product quality and reliability. Test-Data Synthesis: Ability to generate and analyze test data to identify potential issues and validate design solutions. Management Reporting: Strong skills in preparing and presenting clear and concise management reports on project status, risks, and performance. Aerothermal Validation: Knowledge and experience in validating aerothermal performance of automotive components and systems. HVAC Testing: Experience in conducting and analyzing HVAC (Heating, Ventilation, and Air Conditioning) testing for automotive applications. Thermal Performance: Understanding of thermal performance principles and their application to automotive design and testing. CAD Review: Ability to review and analyze CAD (Computer-Aided Design) models to identify potential design flaws or areas for improvement. CFD/1D Simulation Review: Experience in reviewing and interpreting results from Computational Fluid Dynamics (CFD) and 1D simulation models. DVP: Familiarity with Design Verification Plan (DVP) processes and methodologies. Vehicle Instrumentation: Knowledge of vehicle instrumentation systems and their role in data acquisition and analysis. Road Trip Testing: Experience in planning and executing road trip testing to evaluate vehicle performance under real-world conditions. Lab Testing: Proficiency in conducting and analyzing lab testing to evaluate component and system performance. Data Analysis: Strong analytical skills with the ability to interpret data and draw meaningful conclusions. Scorecard: Experience in developing and utilizing scorecards to track and measure project performance. PLM: Familiarity with Product Lifecycle Management ( PLM ) systems and their role in managing product data and processes. Microsoft Suite: Proficient in using Microsoft Suite applications, including PowerPoint , Excel (including Macro capabilities), and Word . Power BI: Experience using Power BI for data visualization and reporting. Analytical Skills: Demonstrated ability to analyze complex problems and develop effective solutions. Problem-Solving Skills: Strong problem-solving skills with the ability to identify root causes and implement corrective actions. Communication Skills: Excellent written and verbal communication skills with the ability to effectively communicate technical information to both technical and non-technical audiences. Leadership: Demonstrated leadership skills with the ability to motivate and inspire teams. Networking Abilities: Ability to build and maintain strong relationships with internal and external stakeholders. What We Offer Salary:

Vehicle Performance Test Engineer

RLE India Private Limited•

Remote

•full time

Job Summary We are seeking a highly motivated and experienced Vehicle Performance Test Engineer to join our team. This role will focus on conducting and analyzing vehicle performance tests, ensuring the quality and performance of our vehicles. Key Responsibilities The Vehicle Performance Test Engineer will be responsible for planning, executing, and documenting vehicle performance tests. This includes conducting various tests related to fuel economy, emissions, vehicle drivability, and transmission performance. The engineer will also be responsible for analyzing test data, identifying areas for improvement, and collaborating with engineering teams to implement solutions. Required Skills & Qualifications Bachelor’s degree in mechanical or Automobile Engineering. 6-8 years of experience in vehicle performance testing. This level of experience indicates a seasoned professional capable of independently planning and executing complex test programs, analyzing results, and contributing to vehicle development. Analytical Skills: Demonstrated ability to analyze complex data and draw meaningful conclusions. Problem-Solving Skills: Proven ability to identify and resolve technical issues related to vehicle performance. Communication Skills: Excellent written and verbal communication skills, with the ability to clearly and concisely communicate technical information to both technical and non-technical audiences. Teamwork: Ability to work effectively as part of a team, collaborating with engineers and other stakeholders to achieve common goals. Data Analysis: Proficiency in data analysis techniques and methodologies. Excel: Advanced proficiency in Excel for data manipulation, analysis, and reporting. MDA: Experience with MDA (Motor Development Analyzer) for vehicle performance analysis. Power BI: Experience using Power BI for data visualization and reporting. Google Slides and Google Sheets: Proficiency in using Google Slides and Google Sheets for presentations and data management. PowerPoint: Proficiency in using PowerPoint for presentations. Vehicle Testing: Comprehensive understanding of vehicle testing methodologies and procedures. DVP Tests: Experience with DVP (Development Verification Plan) tests. Vehicle Coast Down: Expertise in conducting and analyzing Vehicle Coast Down tests. Fuel Economy: Deep understanding of Fuel Economy testing and analysis. Gradeability: Experience in evaluating Gradeability performance. Emission Testing: Knowledge of Emission Testing procedures and regulations. TA & COP: Familiarity with TA & COP (Transmission Application and Calibration Optimization Process). Subjective Assessment: Ability to conduct and interpret Subjective Assessment of vehicle performance. Vehicle Drivability: Experience in evaluating Vehicle Drivability characteristics. Gear Shift Quality: Ability to assess and analyze Gear Shift Quality . Manual Transmission: Understanding of Manual Transmission systems and testing. Automatic Transmission: Understanding of Automatic Transmission systems and testing. Benchmark Vehicle Testing: Experience in conducting Benchmark Vehicle Testing . Root Cause Analysis: Ability to perform Root Cause Analysis to identify and resolve performance issues. Benchmarking: Experience in conducting Benchmarking studies. Data Seeking: Ability to effectively Data Seeking to support analysis and decision-making. Technical Discussions: Ability to participate in and lead Technical Discussions . Calibration: Experience with vehicle Calibration processes. Application Management: Experience in Application Management related to vehicle testing. V Box: Experience using V Box for vehicle performance measurement. Ipetronic: Experience using Ipetronic for engine testing and analysis. L350 Aqua Sensor: Experience using L350 Aqua Sensor for environmental testing. CAN Analyser: Experience using CAN Analyser for vehicle communication analysis. DFL: Familiarity with DFL (Data Flash Loader). INCA: Experience using INCA (IN Control) for ECU calibration and diagnostics. ETAS: Familiarity with ETAS (Electrical Transport and Automotive Systems) products and technologies. What We Offer Salary:

Artificial Intelligence Senior Associate

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team in India. This role is ideal for a candidate with a strong foundation in data science and a passion for leveraging AI/ML to solve complex business challenges within the Technology industry. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, implementation, and maintenance of AI/ML solutions. This includes collaborating with cross-functional teams to identify opportunities for AI/ML applications, designing and building AI/ML models, and ensuring the scalability and reliability of these models in a production environment. The role requires a proactive approach to problem-solving and a commitment to continuous improvement. Required Skills & Qualifications AI/ML : A deep understanding of artificial intelligence and machine learning principles, including various algorithms and techniques for model building, training, and evaluation. Python : Proficiency in Python programming language for data manipulation, statistical analysis, and AI/ML model development. Google Cloud Platform (GCP) : Experience with GCP services, including Big Query , Dataproc , Data Fusion , and Cloud SQL , for data storage, processing, and analysis. Data/Analytics : Strong analytical skills with the ability to extract meaningful insights from large datasets and communicate findings effectively. Automation : Experience in automating data processing and AI/ML workflows to improve efficiency and reduce errors. Business Analysis : Ability to understand business requirements and translate them into technical specifications for AI/ML solutions. Business Transformation : A grasp of how AI/ML can be leveraged to drive business transformation and create competitive advantage. CI/CD : Familiarity with continuous integration and continuous delivery ( CI/CD ) practices for deploying and managing AI/ML models. ETL : Experience with extract, transform, load ( ETL ) processes for data integration and preparation. Jira : Proficiency in using Jira for project management and issue tracking. Data Flow : Understanding of data flow principles and techniques for designing efficient data pipelines. TERRAFORM : Experience with TERRAFORM for infrastructure as code. Tekton : Knowledge of Tekton for container-native CI/CD. AIRFLOW : Experience with AIRFLOW for orchestrating complex data workflows. Airflow PySpark : Ability to utilize Airflow with PySpark for large-scale data processing. POSTGRES : Familiarity with POSTGRES database. API : Understanding of API design and integration. GCP : Comprehensive knowledge of GCP ecosystem. Financial Reporting : Ability to apply AI/ML techniques to financial data and generate insightful reports. Leadership : Demonstrated leadership potential with the ability to guide and mentor junior team members. Strategic Communication : Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences. Communication Skills : Strong written and verbal communication skills. Analytical Skills : Exceptional analytical and problem-solving skills. Problem-Solving Skills : Ability to identify, analyze, and solve complex problems effectively. GitHub : Proficiency in using GitHub for version control and collaboration. Qualifications : A Bachelor's Degree and a Master's Degree are required. Experience Required : We are seeking candidates with 3-9 years of relevant experience in data science or a related field. This level of experience indicates a strong foundation in AI/ML principles and a proven ability to deliver impactful results. What We Offer Salary :