Senior Business Intelligence Analyst

For more than 80 years, our client’s engineers and product specialists have partnered with customers to produce highly engineered connectivity and sensing solutions that make a connected world possible. Their focus on reliability, durability, and sustainability exemplifies their commitment to progress. The unmatched range of their product portfolio enables companies, large and small, to turn ideas into technology that can transform how the world works and lives tomorrow.

Role Description:

• The Continuous Improvement EMIA team reports to Operations Automotive EMIA.
• By providing new generation digital solutions to our Operational teams across EMIA, our team creates full transparency and speed in the ongoing digital & 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.
• The Data Scientist Automotive EMIA will report to the Smart Factory Leader Automotive EMIA. 

Responsibilities: 

• 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.
• 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)
• ·Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.
• 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.
• 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.

Requirements:

Desired candidate & Qualification

• Good understanding of a technology driven manufacturing company.
• Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.
• Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Development experience in programming languages R, Python.
• Knowledge, experience in JAVA scripting
• Excellent pattern recognition and predictive modelling skills.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.
• Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.
• Exposure to recent developments in Deep Learning, Gen AI, Agentic AI domain.
• Database skills, on-premises and cloud based.
• Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.
• Excellent presentation skills in both spoken en written English.
•  Excellent and strong communicator
• The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general.
• Bachelor or master’s in data science
• Team player with a solution focused problem-solving mentality.
• Change agent with high Execution level, including training and coaching talents.
• Passioned about the combination of Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering
• Inspired by and searching actively for new technologies and methods.