
GSEC Process, Tooling & Data Analytics Specialist (m/f/d)
Your Responsibilities
- Analyze, define and continuously improve global GSEC and support-related processes, workflows and interfaces.
- Develop pragmatic process standards, templates, working instructions and governance material that are easy to adopt globally.
- Own and improve tooling concepts for Jira, Confluence, dashboards, reporting solutions and other collaboration platforms.
- Build and maintain KPI structures, dashboards and recurring reports that convert operational data into actionable management insights.
- Perform data analysis to identify trends, bottlenecks, recurring failure patterns, process gaps and improvement opportunities.
- Support automation, digitalization and AI-enablement initiatives that increase transparency, knowledge reuse and operational efficiency.
- Translate stakeholder needs into tool requirements, user stories, improvement backlogs and implementation proposals.
- Represent Product Support process and tooling requirements in cross-functional project discussions, especially during NPI planning, pilot phases and readiness reviews.
- Facilitate cross-functional workshops, retrospectives and improvement activities with Product Support, Field Service, R&D, Quality and Manufacturing.
- Use support case and technical escalation context to ensure that processes and tools solve real operational problems without making this a pure technical support role.
- Support the new product introduction phase by participating in cross-functional meetings and ensuring that Product Support requirements, serviceability needs, documentation needs and operational readiness aspects are considered early enough.
- Contribute to knowledge-management concepts that make lessons learned, troubleshooting information and best practices easier to find and reuse.
- Create meaningful KPI dashboards and reports for backlog, cycle time, response quality, resolution trends, NTF/DFS-related patterns and improvement follow-up.
- Define data views that help teams distinguish symptoms from root causes and prioritize improvement actions based on evidence.
- Improve data quality by clarifying definitions, ownership, input discipline and reporting routines.
- Use analytics to support management reviews, process retrospectives, project follow-up and cross-functional escalation discussions.
- Use data analytics to support NPI readiness decisions, including early visibility of known issues, support risks, documentation gaps and follow-up actions.
- Identify opportunities for automation, AI-assisted knowledge retrieval and predictive indicators for support workload or quality risks.
- Close collaboration with experts from Product Support, Field Service, R&D, Quality and Manufacturing.
- Room for ownership, continuous improvement, skill development and innovative digital solutions.
Your Profile
- Degree in industrial engineering, business administration, computer science, information systems, data analytics or a comparable qualification.
- Experience in process management, business analysis, operations excellence, service management or project management.
- Strong analytical mindset with the ability to structure complex information, identify improvement levers and communicate insights clearly.
- Hands-on experience with Jira, Confluence or comparable workflow and knowledge-management platforms.
- Solid understanding of KPI definition, data quality, reporting logic and dashboard-driven management routines.
- Ability to work with operational data sets and derive practical recommendations for management and teams.
- Excellent communication, moderation and stakeholder-management skills in an international environment.
- Good technical understanding of support or engineering workflows; deep product expert knowledge is helpful but not mandatory.
- Experience participating in cross-functional engineering, NPI, readiness or launch-related meetings and translating support requirements into clear actions.
- Fluent English skills, both written and spoken; German or Japanese language skills are an advantage.
Data Analytics Focus
Nice to Have
- Experience with Power BI, Power Automate, advanced Excel, SQL, Python or comparable analytics and automation tools.
- Knowledge of Lean, Six Sigma, BPMN, process mining, ITIL or service management frameworks.
- Experience in a global service, product support, quality or engineering organization.
- Familiarity with semiconductor test systems or other complex high-tech capital equipment.
- Experience with AI-supported process optimization, knowledge management, chatbot enablement or digital assistant concepts.
Our offer
- Flexibility
- Benefits
- Development
- Fitness
- Security
Flexibility: Flexible and trust-based working hours, 30 vacation days + option for additional vacation days, mobile working, individual part-time models and programs for extended periods of absence
Benefits: Attractive salary, share in Advantest´s success through our exceptionally appealing bonus program as well as numerous subsidies, discounts and offerings (e.g. bike leasing)
Development: Structured onboarding programs and mentoring, development discussions, technical and soft skill trainings, language courses and knowledge sessions
Fitness: Ergonomic working environment, sports and fitness options and events (e.g. Global Challenge) as well as health days
Security: Attractive company pension scheme, comprehensive insurance coverage and support in emergency situations
What We Offer
- A visible global role in Production Service with direct impact on operational transparency, process quality and service efficiency.
- The opportunity to shape scalable tools and data-driven ways of working for an international support organization.
- A collaborative, international team environment with modern tools and flexible ways of working.
If you have any questions, Ann-Kathrin Rupp will be happy to answer them.
AdvantestAnn-Kathrin Rupp
Böblingen
+49 (0) 7031.204.8022
For further information visit: www.advantest-career.de