Data Analyst

This advert was translated automatically from Portuguese. Read the original.

The Bosch Group has more than 400 000 employees around the world, present in 60 countries, and we are proud to impact people's lives and to work towards a more sustainable future. Bosch Car Multimedia, S.A. belongs to the Automotive Electronics division and is focused on making the vehicles our third living space. About 3.600 associates are committed to develop and produce high quality technology that shape change in mobility worldwide. The company' success lies in its highly specialized and innovative team, and on the technological know-how which makes Bosch the leading supplier in the automotive market. At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference in mindsets, cultures, generations, identities and perspectives. Everyone should bring their authenticity and work together respectfully. Bosch is an employer that values diversity and equal opportunities. We welcome applications from people with disabilities and we can provide reasonable accommodations during the recruitment process and in the performance of professional activity. By including everyone and ensuring equal opportunities we unleash our full potential. As a Data Analyst for Manufacturing Technologies, you will work at the intersection of engineering, analytics, and digitalization. By transforming complex data into meaningful insights, you will help drive process improvements, support innovation projects, and enable data-driven decisions across manufacturing and development environments. Your contribution to something big: Analyze and prepare data for impactful decisions - Collect, consolidate, and clean data from various sources, including manufacturing systems, databases, laboratory measurements, development trials, and engineering reports. Collect, consolidate, and clean data from various sources, including manufacturing systems, databases, laboratory measurements, development trials, and engineering reports. - Develop and maintain data preparation and transformation pipelines to ensure high-quality and reliable datasets. Develop and maintain data preparation and transformation pipelines to ensure high-quality and reliable datasets. - Validate data completeness, consistency, and integrity prior to analysis. Validate data completeness, consistency, and integrity prior to analysis. - Create standardized datasets that support recurring engineering and operational analyses. Create standardized datasets that support recurring engineering and operational analyses. Generate insights and solve engineering challenges - Analyze production and development data to identify trends, anomalies, relationships, and opportunities for improvement. Analyze production and development data to identify trends, anomalies, relationships, and opportunities for improvement. - Support troubleshooting and problem-solving activities using statistical and analytical methods. Support troubleshooting and problem-solving activities using statistical and analytical methods. - Conduct root cause investigations based on quantitative data analysis. Conduct root cause investigations based on quantitative data analysis. - Evaluate process stability, capability, variability, and performance using statistical techniques. Evaluate process stability, capability, variability, and performance using statistical techniques. - Support process optimization initiatives through data-driven recommendations and performance monitoring. Support process optimization initiatives through data-driven recommendations and performance monitoring. Create meaningful visualizations and reporting solutions - Design, develop, and maintain interactive dashboards and reports using Power BI, Tableau, or similar Business Intelligence tools. Design, develop, and maintain interactive dashboards and reports using Power BI, Tableau, or similar Business Intelligence tools. - Transform complex analytical findings into intuitive visualizations and actionable insights. Transform complex analytical findings into intuitive visualizations and actionable insights. - Communicate results effectively to both technical and non-technical stakeholders. Communicate results effectively to both technical and non-technical stakeholders. - Contribute to the standardization of KPIs and reporting structures across projects and manufacturing technologies. Contribute to the standardization of KPIs and reporting structures across projects and manufacturing technologies. Collaborate across multidisciplinary teams - Work closely with Process Experts, Technology Developers, and Project Teams to understand business and engineering requirements. Work closely with Process Experts, Technology Developers, and Project Teams to understand business and engineering requirements. - Define, monitor, and continuously improve performance indicators for manufacturing technologies and development projects. Define, monitor, and continuously improve performance indicators for manufacturing technologies and development projects. - Enable informed and data-driven decision making through timely analyses and insights. Enable informed and data-driven decision making through timely analyses and insights. - Support development, industrialization, and continuous improvement activities across engineering teams. Support development, industrialization, and continuous improvement activities across engineering teams. Drive automation and continuous improvement - Automate recurring analyses and reporting processes using Python, SQL, and Business Intelligence tools. Automate recurring analyses and reporting processes using Python, SQL, and Business Intelligence tools. - Identify opportunities to enhance existing data collection, reporting, and analytics workflows. Identify opportunities to enhance existing data collection, reporting, and analytics workflows. - Promote best practices in data analysis, visualization, and data management. Promote best practices in data analysis, visualization, and data management. - Contribute to reusable analytical solutions and standards that support manufacturing excellence and Industry 4.0 initiatives. Contribute to reusable analytical solutions and standards that support manufacturing excellence and Industry 4.0 initiatives. What distinguishes you: Education - Master's degree in Mathematics, Statistics, Data Analytics, Engineering, Economics, Physics, Computer Science, or a related field. Experience - Experience in Data Analytics, Business Analytics, Industrial Analytics, Engineering Analytics, or a similar field. Experience in Data Analytics, Business Analytics, Industrial Analytics, Engineering Analytics, or a similar field. - Experience working with large and complex datasets. Experience working with large and complex datasets. - Experience creating dashboards and reports that support business and engineering decisions. Experience creating dashboards and reports that support business and engineering decisions. - Practical experience using Python for data preparation, automation, and analysis. Practical experience using Python for data preparation, automation, and analysis. - Experience collaborating with multidisciplinary and technical teams. Experience collaborating with multidisciplinary and technical teams. - Experience in manufacturing or industrial environments is considered an advantage. Experience in manufacturing or industrial environments is considered an advantage. Know-how - Data Analytics & Statistics Data Analytics & Statistics - Strong understanding of statistical analysis and data interpretation. Strong understanding of statistical analysis and data interpretation. - Knowledge of hypothesis testing, probability distributions, confidence intervals, regression analysis, and correlation analysis. Knowledge of hypothesis testing, probability distributions, confidence intervals, regression analysis, and correlation analysis. - Understanding of process variability, process capability, and performance measurement. Understanding of process variability, process capability, and performance measurement. - Ability to translate engineering and business requirements into analytical solutions. Ability to translate engineering and business requirements into analytical solutions. - Programming & Data Management Programming & Data Management - Strong SQL skills. Strong SQL skills. - Good experience with Python for data analysis, automation, and visualization, including libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn. Good experience with Python for data analysis, automation, and visualization, including libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn. - Experience working with structured and semi-structured datasets. Experience working with structured and semi-structured datasets. - Understanding of data quality principles, data modelling concepts, and relational databases. Understanding of data quality principles, data modelling concepts, and relational databases. - Data Visualization Data Visualization - Experience with Power BI, Tableau, or comparable BI platforms. Experience with Power BI, Tableau, or comparable BI platforms. - Ability to create intuitive dashboards and impactful data visualizations. Ability to create intuitive dashboards and impactful data visualizations. - Experience presenting analytical insights to both technical and non-technical audiences. Experience presenting analytical insights to both technical and non-technical audiences. Languages - Good communication skills in English. Working Style and Methods - Structured, analytical, and detail-oriented approach to work. Structured, analytical, and detail-oriented approach to work. - Ability to manage multiple priorities in a dynamic environment. Ability to manage multiple priorities in a dynamic environment. - Proactive mindset with a passion for continuous improvement. Proactive mindset with a passion for continuous improvement. - Ability to work autonomously while collaborating effectively with cross-functional teams. Ability to work autonomously while collaborating effectively with cross-functional teams. - Strong communication and stakeholder management skills. Strong communication and stakeholder management skills. Personality - Curious and eager to learn. Curious and eager to learn. - Solution-oriented and collaborative. Solution-oriented and collaborative. - Passionate about using data to solve real-world engineering challenges. Passionate about using data to solve real-world engineering challenges. - Motivated to drive innovation and improve manufacturing performance. Motivated to drive innovation and improve manufacturing performance. Work #LikeABosch includes: ⚖️ Flexible work conditions 🔀 Hybrid work system 🌐 Exchange with colleagues around the world 🛡️ Health insurance 🧑‍⚕️ Medical office (psychology and general clinic) & Social Services Office on site 📚 Training opportunities (p.e., technical training, foreign languages training) & certifications 📈 Opportunities for career progression and continuous professional development 💲 Access to great discounts in partnerships and Bosch products 🏋️ Sports and health related activities 🚉 Great access to public transports 🚌 Free transport from Porto 💰 Flexible benefits platform 🅿️ Free parking lot 🍽️ Canteen Success stories don´t just happen. They are made... Make it happen! We are looking forward to your application! Requirements - Master's degree in Mathematics, Statistics, Data Analytics, Engineering, Economics, Physics, Computer Science, or a related field - Experience working with large and complex datasets - Experience creating dashboards and reports that support business and engineering decisions