Sourcing Support - Master Data

Senior Business Intelligence Analyst

Senior - Data Engineer

Central Demand Planner

Financial Analyst

Manager, Data Science (GNS)

Responsibilities: <ul><li>Establish and maintain data quality metrics and KPIs, regularly monitoring and reporting on data quality issues, trends, and improvements (also in VBA, SQL)</li><li>Collaborate with stakeholders, including supply chain planners, IT teams, and business leaders, to identify master data requirements and define data governance policies and procedures.</li><li>Lead the identification, collection, and validation of master data from various sources, ensuring data accuracy and integrity throughout the data lifecycle.</li><li>Define and implement data cleansing, enrichment, and standardization processes to improve data quality and usability.</li><li>Drive the adoption and utilization of master data management tools and systems, providing guidance and support to users, and ensuring data integrity and consistency across platforms.</li><li>Collaborate with IT teams to design, implement, and enhance master data management systems and infrastructure, aligning with business requirements and best practices.</li><li>Provide guidance and training to supply chain planning teams on master data management processes, standards, and tools, promoting data governance awareness and adherence.</li><li>Stay updated on industry trends, best practices, and emerging technologies related to master data management, and proactively identify opportunities for improvement and innovation.</li><li>Lead data-related projects and initiatives, coordinating cross-functional teams, managing timelines and deliverables, and ensuring successful project execution.</li></ul> Requirements: Education, Technical Qualification &amp; Experience: <ul><li>Bachelors degree in Supply Chain Management, Business Administration, Information Systems, or a related field.</li></ul> Professional Experience (years in what processes and function): <ul><li>Proven experience 1-2 years master data management, data governance, or a related field, preferably in a supply chain planning environment.</li><li>Strong knowledge of supply chain planning processes, including demand planning, inventory management, and production planning.</li><li>Proficiency in utilizing master data management tools and systems (e.g., SAP, Tableau, VBA, SQL.).</li><li>Solid understanding of data governance principles, data quality management, and data lifecycle management.</li></ul> Special Qualifications, Knowledge &amp; Skills: <ul><li>Experience with data analysis and reporting, using tools such as Excel, Tableau, or Power BI.</li><li>Excellent analytical and problem-solving skills, with a keen attention to detail. Need to be detail oriented and able to communicate to cross functional teams.</li><li>Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.</li><li>Ability to work in a fast-paced and dynamic environment, managing multiple priorities and deadlines effectively.</li></ul>

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>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>

Responsibilities: <ul><li>Lead the Global Demand Planning Cycle of the S&amp;OP process: Own and execute the monthly demand process from system handover to consensus sign-off. </li><li>Coordinate inputs from Sales, Product Management, and Finance, and ensure outputs feed into supply planning and S&amp;OP.</li></ul> Improve Forecast Accuracy:&nbsp; <ul><li>Drive measurable improvements in MAPE, Bias, and Forecast Adherence. Use data-driven techniques and root-cause analysis to understand gaps and implement corrective actions.</li></ul> Bridge Strategy and Execution:&nbsp; <ul><li>Translate commercial assumptions and market intelligence into an aligned, actionable forecast that drives capacity, procurement, and financial planning.</li></ul> Advance Tools and Reporting:&nbsp; <ul><li>Develop and maintain robust forecasting reports and KPIs using Excel, Power BI (or Tableau), and SAP IBP. </li><li>Push the team toward automated, visual, and insightful reporting.</li><li>Facilitate Consensus and Governance: Orchestrate monthly consensus meetings and prepare executive-ready materials that clearly communicate changes, assumptions, and risks.</li></ul> Support Constrained Planning:&nbsp; <ul><li>Collaborate with the Supply Planner to identify constraint-driven adjustments and simulate scenarios to evaluate trade-offs.</li><li>Enhance Collaboration and Accountability: Act as the single point of contact for demand planning across regions. Push for timely inputs, challenge assumptions, and ensure cross-functional accountability.</li></ul> Lead Process Improvements:&nbsp; <ul><li>Identify inefficiencies and design solutions—whether it’s template optimization, system enhancements, or training stakeholders on best practices.</li></ul> Support S&amp;OP Strategy:&nbsp; <ul><li>Contribute actively to the broader S&amp;OP cycle, including confidence-level strategies, forecast version control, and long-range planning exercises.</li></ul> Requirements: <ul><li>Bachelor’s degree in supply chain, Engineering, Business, or related field; Master’s preferred</li><li>Minimum 5 years of experience in demand planning or S&amp;OP in a multinational environment</li><li>Demonstrated ability to work independently and proactively influence cross-functional teams</li><li>High proficiency in Excel and Power BI (or Tableau); experience with SAP IBP is strongly preferred</li><li>Strong business acumen and communication skills; able to translate data into decisions</li><li>Fluent in English</li></ul>

Responsibilities: Responsible for ensuring timely and quality financial planning and reporting, including: <ul><li>IT Cost Reporting</li><li>Departmental Spending</li><li>IPRB / Rationalisation / Cost Saving</li><li>Financial Review package Scrap</li><li>Spending analysis for Actual vs Outlook vs Budget for various areas such as: Operations, Factory support, R&amp;D, S&amp;M, G&amp;A expenses, etc and identify opportunities for cost improvement.</li><li>Analyze financial results and highlight key trends, variances, and risks.</li><li>Provide insights into revenue, expenses, and profitability performance</li><li>Prepare Quarterly Outlook / Yearly Budget for:</li><li>Operations, Factory support, R&amp;D, S&amp;M, G&amp;A expenses forecast)IT spending</li><li>IPRB / Rationalisation / Cost Saving Scrap</li><li>Ad hoc projects - Process Automation / Improvement</li></ul> Requirements: <ul><li>Degree in Engineering / Accountancy/ Business Admin</li><li>2 to 3 years of Finance, Accounting, or related work experience.</li><li>Proficient in Microsoft office skill, preferably knowledge of SAP</li><li>Knowledge of VBA Excel Programming and Tableau application will be an added advantage.</li><li>Able to work under Stressful environment &amp; tight deadline</li><li>Good in planning and organizational and analytical skill</li><li>Proactive and good problem-solving skills</li><li>Possess good interpersonal and communication skills</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions.</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high-bar for model development.</li></ul> Requirements: <ul><li>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have significant experience in managing larger Technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

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Sourcing Support - Master Data

Senior Business Intelligence Analyst

Senior - Data Engineer

Central Demand Planner

Financial Analyst

Manager, Data Science (GNS)

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Sourcing Support - Master Data

Senior Business Intelligence Analyst

Senior - Data Engineer

Central Demand Planner

Financial Analyst

Manager, Data Science (GNS)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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