Technical Lead, Data, AI & Analytics (m/f/d)

Job ID: 41698  |  Location: Munich, Bavaria, Germany | Work Model: Hybrid  Clariant is a focused, sustainable, and innovative specialty chemical company. We connect our customers to value-adding and sustainable solutions for products used in countless everyday applications. Our solutions contribute to our customers' sustainability targets while prioritizing our own. We are committed to creating value through innovation and sustainability for our customers, stakeholders, and the environment. As Technical Lead, Data, AI & Analytics, you are the technical backbone of the business unit's digital build-up. You own the BU’s growing portfolio of ML/AI applications and the architecture of the BU's data lake, drive the development backlog as technical product owner alongside business counterparts, and set the engineering standards that separate production-grade solutions from prototypes. The role sits at the intersection of solution design and data architecture in an industrial environment where ERP, CRM, MES, and plant data are daily reality. Responsibilities Act as technical product owner for the development backlog: refine user stories with business solution and domain owners, translate business requirements into technically sound, appropriately scoped work, and drive weekly prioritization and sprint planning Own the solution architecture for ML/AI applications and digital products built by the team, establishing the design principles, technology choices, and reusable patterns that keep solutions scalable, maintainable, and production-ready Apply strong ML/AI judgment to scope and validate solution approaches — knowing when a problem needs a model, which class of methods fits, and what production-ready realistically requires  Design the concept and drive the implementation of the business unit's cloud data lake, e.g., data models, ingestion patterns, storage and access layers Ensure solutions integrate cleanly with the industrial systems landscape (ERP, MES, historians, LIMS, CRM) and the cloud platform Establish and uphold engineering standards across the team's development work: code and architecture reviews, pull request discipline, testing and CI/CD gates, MLOps and model lifecycle management Provide indirect technical leadership to data scientists, ML engineers, and developers across project teams through mentoring, design reviews, and technical direction-setting Continuously evaluate emerging technologies — cloud-native data platforms, generative AI, ML tooling and selectively introduce those that create genuine value in an industrial manufacturing context Requirements Master's or PhD in Computer Science, Data Science, Engineering, Applied Mathematics, or a related STEM field, with 8+ years spanning data science/ML and software engineering, including 3+ years in a technical lead or architect role Proven track record delivering production-grade AI/ML systems in an industrial or…