Complexity Management Analyst

Analyst - Complexity Management

Role Summary

The Analyst in Engineering supports the Global AA Complexity Management, Value Engineering, and TCM team by translating complex product and process inputs to deliver actionable analytics, dashboards, and digital solutions that drive cost reduction, portfolio optimization, and digitalized R&D processes.

Main Tasks

Complexity Management Process

• Define and ensure Product Family Standards which are described in development handbooks and internal standards.
• Develop and improve the product related data architecture. Focus on product classifications as well as master data and product specifications to cluster portfolios and product families.

Product Portfolio and Product Analytics

• Identify patterns, trends, and insights from multiple inputs sources (SAP, PDM, etc.) to provide actionable recommendations for product and component consolidation.
• Use Power BI or equivalent tools to visualize component and product portfolios and propose savings opportunities, e.g., through similarity analysis.
• Define, request, govern, and continuously improve data quality in R&D and other relevant data sources.
• Act as a subject matter expert within the global team, providing support and guidance wherever specific expertise is required.

 Digitalization of Global AA R&D Processes

• Conceptualize, define, and build efficient digital end‑to‑end processes within Global AA R&D.
• Drive project initiation and implementation of digitalization initiatives.
• Document and continuously optimize digitalized solutions.

 Communication on Insights and Recommendations

• Create compelling visualizations and reports that clearly communicate data‑driven insights to stakeholders.
• Present findings with a clear point of view to influence and support business strategy.
• Create and maintain dashboards for global reporting, including KPIs (e.g., AA Cost Hunting, Technical Change Management, Complexity Management).

 Collaboration and Network

• Work closely with engineers within the team and collaborate cross‑functionally across PSOs/BUs.
• Internal stakeholders: AA Engineering, OE Engineering, TE, IT, PMO, Operations, Quality, Purchasing, Sales, Product Management, Logistics.
• External stakeholders: Consultants, software providers, and academic or research partners.

 

Skills

DigitalizationProject ManagementRequirements AnalysisData AnalysisStrategic Cost ReductionBudgetingKPI ManagementCross-Functional UnderstandingAgile MethodologyComplexity Management

Experience

• Bachelor’s or master’s degree in engineering, Mathematics, Statistics, Business Analytics, or a related technical discipline.
• Minimum 3 years of relevant experience in product analytics, engineering data management, or digitalization roles within an industrial or manufacturing environment.
• Strong experience with enterprise systems, including SAP and product management databases (e.g., CIM-Database/PDM).
• Advanced proficiency with the Microsoft Power Platform, especially Power BI (data modeling, DAX), and familiarity with Power Apps and Power Automate for workflow digitalization.
• Solid analytical and information/data processing skills, including experience with Excel (advanced), and basic scripting (e.g., Python, SQL, or equivalent)
• Experience in engineering or R&D environments and enthusiasm for digitalization, process automation, and modern engineering tools.
• Strong communication and stakeholder‑management skills to translate technical insights into clear business recommendations.
• Motivation to develop competencies in AI/ML and their application in engineering analytics.
• Fluent in English; German language skills are an advantage.

 

Experience Level

Mid Level