Senior Business Intelligence Analyst

Associate Data Engineer

Senior - Data Engineer

Quality Improvement Manager

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

 IIAD / SAD / LAD Artificial Intelligence Engineer

Lead AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

Role Description: <ul><li>The Continuous Improvement EMIA team reports to Operations Automotive EMIA.</li><li>By providing new generation digital solutions to our Operational teams across EMIA, our team creates full transparency and speed in the ongoing digital &amp; lean transformation(s), which will enable all involved functions to leverage data to develop business insights and roadmap updates based upon clearly arranged and understandable data. Due to the extended scope, focusing also on the connecting processes from Supplier(s) to Manufacturing ending at the Customer(s) (internal and external) we will function as ‘the’ differentiator for our Company.</li><li>The Data Scientist Automotive EMIA will report to the Smart Factory Leader Automotive EMIA.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Lead projects and work together with our Automotive EMIA Operations plants, internal (IT, , Corporate Technology, CoE, SC, ..) and external partners in the area of Smart Factory (Applications, ML, AI, DL), aligned with Operations Automotive EMIA Strategy.</li><li>Lead Smart Factory improvement projects (Enhancements) of existing applications together with internal / external supplier and customers (project management) until the level of RTD (Ready To Deploy)</li><li>·Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.</li><li>Identify and interpret data sources, manage large amounts of data, merge data sources together, ensure consistency of datasets, create visualizations to aid in understanding data.</li><li>Develop, Validate and Deploy (including Training and Coaching of the users) until the level of RTD (Ready To Deploy), Digital Factory Applications, ML models, contributing to waste elimination and efficiency improvements within all Operations functions (Manufacturing, Quality, SC, LOG, ….), this together with our internal and external partners.</li></ul>&nbsp;Requirements: Desired candidate &amp; Qualification <ul><li>Good understanding of a technology driven manufacturing company.</li><li>Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.</li><li>Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..</li><li>Good applied statistics skills, such as distributions, statistical testing, regression, etc.</li><li>Development experience in programming languages R, Python.</li><li>Knowledge, experience in JAVA scripting</li><li>Excellent pattern recognition and predictive modelling skills.</li><li>Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.</li><li>Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.</li><li>Exposure to recent developments in Deep Learning, Gen AI, Agentic AI domain.</li><li>Database skills, on-premises and cloud based.</li><li>Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.</li><li>Excellent presentation skills in both spoken en written English.</li><li>&nbsp;Excellent and strong communicator</li><li>The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general.</li><li>Bachelor or master’s in data science</li><li>Team player with a solution focused problem-solving mentality.</li><li>Change agent with high Execution level, including training and coaching talents.</li><li>Passioned about the combination of Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering</li><li>Inspired by and searching actively for new technologies and methods.</li></ul>

Responsibilities: <ul><li>Ability to troubleshoot problems in a live environment and provide real time help with critical issues.</li><li>Write code that is easily understood and maintainable by other team members.</li><li>Keep up to date with developments in technologies we are using.</li><li>Ability to communicate and work effectively, supporting various business departments.</li><li>Ability to work in fast-paced interdisciplinary environment.</li></ul> Requirements <ul><li>BA/BS in Computer Science or equivalent practical experience.&nbsp;</li><li>At least 3+ years of post-university experience as a full-stack engineer.</li><li>Solid knowledge of programming fundamentals—algorithms, data structures, design patterns, and paradigms.</li><li>Strong knowledge of Python.</li><li>Solid knowledge SQL and relational databases.</li><li>Knowledge of Extract-Transform-Load (ETL) and big data analytics tools.</li><li>Experience working in a cloud environment (AWS, Azure, GCP).</li><li>Familiarity with popular Python data analytics frameworks.</li><li>Familiarity with Snowflake or other large analytics engines.</li><li>Experience with data warehousing and working in environments with large scale, complex analytics requirements.</li><li>Familiarity with DAG-based job scheduling tools.</li><li>Cloud-native container orchestration platforms and tools.</li><li>Experience working in the Financial Services industry.</li></ul>

Responsibilities: <ul><li>Uses a set of tasks and techniques to work as a liaison among and elicit the needs of stakeholders to define and validate solutions that meet business needs, goals, or objectives.</li><li>Analyzes and synthesize information elicited from stakeholders, defines, and manages the plan to deliver requirements and documents, and manages requirements throughout the project life cycle.</li><li>Develop ETL (Extract, transform, load) process to help extract and manipulate data from multiple sources.</li><li>Reformulating or automating the existing data workflows to maximize their functioning and greater scalability.</li><li>Critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, and produce actionable business insights out of it.</li><li>Need to conduct complex data analysis and improve data quality and efficiency.</li><li>Develop models to create reporting infrastructure/dashboards for business process management and data mining.</li><li>Design Summary, Detail, and Dashboard reports and management summaries which present data findings in a professional, concise, and readable format appropriate for content and audience.</li><li>Solve ad-hoc requirements of Management related to data for critical decision making</li><li>Troubleshoot data inaccuracies, identify root causes, and take corrective action</li><li>Effectively communicate and translate quantity findings (Storytelling with data) inclusive of key insights and actionable recommendations to optimize performance</li><li>Optimize reports to ensure a responsive solution when visualizing vast amounts of data.</li></ul> Requirements: <ul><li>5+ years of data engineering experience in ETL design, development, optimization &amp; testing using, Alteryx, Data Bricks, Cloud AWS Services, Python, SQL scripts,</li><li>5+ years of hands-on experience in business intelligence and in configuring, designing, and building visualizations and dashboards using Tableau and other BI tools (Tableau Prep, Tableau Dashboard, Tableau Server, Business Objects, Power BI, etc.)</li><li>Excellent problem-solving, communication, and organizational skills.&nbsp;</li><li>Experience in performance tuning and optimization of ETL processes to enhance efficiency and minimize data processing time</li><li>Detail-oriented with excellent time management and organizational skills to meet a critical deadline</li><li>Self-motivated, ability to prioritize work and multi-task across many assignments in a fast-paced work environment</li><li>Collaborated with cross-functional teams to gather requirements, design data models, and implement scalable data architectures to support business analytics and reporting needs</li><li>Proven ability to work independently and with a team.</li><li>Ability to interpret technical or dashboard structure</li><li>Experience in business domains – supply chain, pricing, sales &amp; marketing, sales, finances</li></ul>

Role Information: <ul><li>The Quality Improvement Manager is responsible to drive and support improvement activities and convergent Problem-Solving competencies within AUT ASEAN, leveraging scalable methodologies and digital tools while unleashing people’s talent.</li><li>Working in collaboration with production plant at Gateway Thailand towards waste reduction and improving Incidents on our customer base.&nbsp;</li><li>She/he is the Leader in ASEAN Problem Solving Committee and leads cross functional teams to solve complex and difficult manufacturing and quality problems.</li><li>She/he contributes to the project selection that will have the highest impact on plant metrics.</li><li>She/he coaches plant problem solvers and ensures their development</li></ul> Responsibilities: <ul><li>Leader in ASEAN Problem Solving (PS) Committee.</li><li>Organize regular meeting review status &amp; planning.</li><li>Promote PS culture throughout the Plant and ASEAN at all levels.</li><li>Promote the selection of the projects that will have the highest impact on plant metrics (eg. CoPQ) and manage all PS projects including PS initiatives from Line QRM escalation to VSM/Plant Level.</li><li>Support production improvement process through PS projects.</li><li>Lead cross-functional team to apply diligently a structured problem-solving methodology that best fits the situation (Shainin, SPS, Six Sigma or other equivalent methods as described by the Shifting Gears)</li><li>Follow up all PS projects with project owner and provide coaching to ensure PS methodologies are correctly applied.</li><li>Regular project coaching with PS Master from Global, and follow-up to project closure and realize saving.</li><li>Proactively anticipate roadblocks to find solutions and escalate when needed.</li><li>Report out project progress, people development and savings to PS Committee and Management.</li><li>Tabulate and manage Plant/ASEAN people PS skill matrix and identify training needs, plan &amp; execution.</li><li>Coach, Develop and Expand local Problem Solver Practitioners.</li><li>Represent ASEAN in PS matter and report status to regional and global level.</li><li>Alignment with AP and Global PS leaders for new PS initiatives and execution.</li><li>Any other assignments as delegated by reporting Manager.</li></ul> Requirements: <ul><li>Engineering degree (Mechanical or Electrical Engineering).</li><li>Strong understanding of 6 Sigma tools and Minitab usage.</li><li>Strong understanding of engineering fundamentals and product design</li><li>Experience in taking project using structured problem-solving methodology (Shainin Red-X, 6 Sigma, etc).</li><li>Experience in coaching and training.</li></ul> Specific Requirements(Mandatory): <ul><li>Certified Red X Master or Master Candidate (ability to coach) or Kepner-Tregoe.</li><li>Strong understanding of 6 Sigma tools and Minitab usage.</li><li>Able to develop Dashboard (PowerBI) and to apply Data Science (Python, R).</li></ul>

Responsibilities: <ul><li>Develop distributed system architecture and system integration&nbsp;&nbsp;</li><li>Design event-driven applications leveraging microservices architecture on cloud platform&nbsp;</li><li>Carry out Model and assess complex IT solutions&nbsp;&nbsp;</li><li>Work closely with platform engineers and other IT professionals to choose compatible design solutions&nbsp;</li><li>Manage and comply with release management process&nbsp;</li><li>Analyze the scope and expected organizational impact of information systems&nbsp;</li><li>Evaluate existing systems and provide advice on how to meet organizational requirements&nbsp;</li><li>Ensure that the technical components of the project are in sync with the business needs of the organization&nbsp;</li><li>Ensure that information systems are secure from threat&nbsp;</li><li>Provide advice on project design, project costs, and expected benefit&nbsp;</li><li>Identifies technical debt and proactively recommends alternatives or improvements&nbsp;</li></ul> Requirements: <ul><li>University degree in Computer Science, Computer Engineering or related subjects preferred&nbsp;&nbsp;</li><li>8+ years of work experience building applications&nbsp;</li><li>Advanced understanding of IT infrastructure and enterprise architectures&nbsp;</li><li>Proven experience with microservices-based architecture&nbsp;</li><li>Proficiency in coding with modern programming languages such as C#, Python, or Node.js&nbsp;</li><li>API-first development experience&nbsp;</li><li>Experience with Cloud Computing (Azure preferable)&nbsp;</li><li>Extensive expertise in any modern document-oriented database, with a preference for MongoDB&nbsp;</li><li>Experience in developing components for Event-Driven Architecture, with a minimum of production-level experience using Event Hubs or Event Grid (or similar technologies like Kafka)&nbsp;</li><li>Experience working in an agile environment with a focus on engineering practices like testing, continuous integration, etc.&nbsp;</li><li>Good knowledge of virtualization&nbsp;&nbsp;</li><li>Analytics mindset with critical thinking and problem-solving skills&nbsp;</li><li>Fine knowledge of industry trends and emerging technologies&nbsp;</li><li>Fluent in English&nbsp;</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: Agentic AI Development:&nbsp;&nbsp; <ul><li>Design, build, and deploy agentic AI systems using frameworks such as LangChain, Lang Graph, and related libraries.&nbsp;&nbsp;</li><li>Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.&nbsp;</li></ul> RAG Pipelines:&nbsp; <ul><li>Implement and optimize retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.&nbsp;</li></ul> LLM Engineering:&nbsp; <ul><li>Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.&nbsp;</li><li>Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.&nbsp;</li></ul> Enterprise AI Platform:&nbsp; <ul><li>Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.&nbsp;</li><li>Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.&nbsp;</li></ul> MLOps &amp; Observability:&nbsp; <ul><li>Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.&nbsp;</li><li>Applied AI Prototyping:&nbsp;</li></ul> Rapidly prototype, experiment, and iterate to improve AI agent capabilities.&nbsp; Collaboration &amp; Research:&nbsp; <ul><li>Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.&nbsp;</li><li>Collaborate effectively with other engineers, researchers, and data scientists.&nbsp;</li><li>Contribute to the documentation and standardization of technical code and practices.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.&nbsp;</li><li>5+ years overall experience in software development, data science, or machine learning.&nbsp;</li><li>1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.&nbsp;</li><li>1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.&nbsp;</li></ul>

Responsibilities: <ul><li>Oversee the design, development, and deployment of AI models and intelligent agents.</li><li>Ensure engineering best practices in model development, testing, and deployment.</li><li>Collaborate with IT and data teams to ensure scalable and secure integration of AI solutions.</li><li>Work closely with business and technical stakeholders to understand requirements and deliver impactful AI solutions.</li><li>Communicate effectively with global teams, bridging technical and business perspectives.</li><li>Support change management and adoption of AI tools across business units.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI&nbsp;</li></ul> Requirements: Basic Qualifications:<ul><li>10+ years of experience in software engineering, data science, AI, or a related field.</li><li>2+ years of experience in leadership role managing technical teams.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS. </li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Bachelor’s or master’s in computer science, Mathematics, Statistics, or a related field.</li></ul> Preferred Qualifications:<ul><li>Experience working in a global enterprise or matrixed organization.</li><li>Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tools.</li><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Experience in applications to sales, marketing, and market research&nbsp;</li></ul>

Responsibilities: <ul><li>Together with the team of developers handle the product quality.</li><li>Lead and manage the automation testing efforts and deliverables.</li><li>Plan and prioritize testing activities.</li><li>Maintain and improve an existing test automation framework.</li><li>Develop automation tests for API and UI.</li><li>Execute, maintain and update automation tests.</li><li>Review and analyze tests execution results.</li><li>Maintain all related test documentation.</li><li>Prepare testing data.</li><li>Proactively acquire and clarify requirements as necessary.</li><li>Mentor less skilled teammates and newcomers.</li></ul> Requirements: <ul><li>Strong knowledge of OOP (understanding OOP in automation).</li><li>Excellent knowledge of automation testing principles.</li><li>Excellent knowledge of web-based application structure.</li><li>Excellent knowledge of Python programming language.</li><li>Expert in REST API testing.</li><li>Experience in UI testing.</li><li>Wide experience in developing automation testing frameworks.</li></ul>

Responsibilities: <ul><li>Client is seeking a skilled Business Intelligence Developer to design, build, and maintain enterprise-scale data products and data sources using platforms like Tableau and Streamlit.</li><li>The ideal candidate will be a detail-oriented developer with strong technical skills who can translate business requirements into robust analytical solutions.</li><li>This role requires a mixture of business acumen and technical expertise, along with an ability to build strong partnerships and collaborate to solve problems.</li><li>Design, develop, and maintain interactive data products and reports in Tableau, Streamlit, and other BI tools.</li><li>Build and optimize data sources, ensuring data integrity and performance at enterprise scale</li><li>Collaborate with business stakeholders to gather requirements and translate them into technical specifications.</li><li>Develop scalable data product solutions that can accommodate growing user bases and data volumes.</li><li>Implement best practices for data product design, data modeling, and visualization techniques.</li><li>Monitor data product performance and user adoption, making improvements as needed.</li><li>Maintain documentation for data products, data sources, and development processes.</li><li>Troubleshoot and resolve technical issues with existing data products and data connections.</li><li>Support data governance initiatives by ensuring consistent data definitions and calculations across reports.</li><li>Participate in code reviews and maintain version control for BI development projects.</li><li>Stay current with BI tool updates and emerging visualization technologies.</li><li>Provide technical support to end users and assist with data product-related questions.</li><li>Contribute to the development of reusable components and templates for efficiency gains.</li></ul> Requirements: Qualifications <ul><li>3+ years in the data space as an analyst, engineer, or equivalent.</li><li>3+ years experience designing, implementing, operating, and extending enterprise dimensional models.</li><li>3+ years working with a large-scale data warehouse, preferably in a cloud environment.</li><li>3+ years of hands-on experience developing data products and reports in Tableau, including advanced calculations, parameters, and complex visualizations.</li><li>Experience with Streamlit or similar Python-based data product frameworks.</li><li>Experience with modern data stack technologies including cloud data warehouses (AWS/Snowflake) and ELT tools.</li><li>1+ years maintaining a project workstream to identify tasks, milestones, and deliverables.</li><li>Bachelors degree in Computer Science, Information Systems, Mathematics,</li></ul>

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38 python scripting Jobs found

Senior Business Intelligence Analyst

Associate Data Engineer

Senior - Data Engineer

Quality Improvement Manager

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

IIAD / SAD / LAD Artificial Intelligence Engineer

Lead AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

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38 python scripting Jobs found

Senior Business Intelligence Analyst

Associate Data Engineer

Senior - Data Engineer

Quality Improvement Manager

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

IIAD / SAD / LAD Artificial Intelligence Engineer

Lead AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

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