Staff Specialist Data Science & Machine Learning iv)*

• End-to-End Forecasting Lifecycle: Design, develop, and continuously optimize time-series forecasting models that translate complex business requirements into robust, scalable solutions for enterprise planning.
• Model Innovation & Quality Assurance: Define rigorous evaluation frameworks and explore advanced techniques to enhance forecast accuracy, ensuring a balance between model complexity, interpretability, and operational feasibility.
• Scalable Architecture: Architect reusable forecasting concepts and pipelines capable of adapting across diverse planning horizons, product lines, and volatile business environments.
• Performance Optimization: Drive continuous quality improvements by systematically analyzing model performance, integrating new data signals, and iterating based on structured feedback loops.
• Strategic Stakeholder Partnership: Act as a trusted technical counterpart to planners and domain experts, translating complex analytical results into clear, actionable insights that align with decision workflows.
• User-Centric Continuous Improvement: Champion the user voice by collecting feedback on forecasting outputs and proactively identifying opportunities to refine analytical processes and future product enhancements., As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener. Are you in?

Do you have experience in Virtualization?, With your Passion for new technologies and your entrepreneurial mindset you help to shape future AI-driven solutions.

• Education & Experience: Hold a degree in Data Science, Computer Science, or Business Analytics, backed by at least 3 - 5 years relevant professional experience in data science, forecasting, or ML engineering.
• Advanced Analytics Expertise: Possess a strong command of AI/ML concepts, including global time-series forecasting, GenAI, and decision intelligence.
• Model Evaluation Proficiency: Demonstrate expertise in rigorous model evaluation techniques, such as backtesting, error metrics analysis, and robustness/bias checks.
• Technical Programming Skills: Maintain high proficiency in Python, with additional knowledge of other programming languages being a distinct advantage.
• Platform Familiarity: Have practical experience with data virtualization, orchestration, and analytics platforms (e.g., Dataiku, Denodo, Hadoop, Spark, Kafka, Openshift).
• Analytical & Communication Strength: Exhibit strong problem-solving abilities and the communication skills necessary to collaborate effectively with both technical teams and non-technical stakeholders.