Role overview
- Design and implement optimization and simulation models to solve business challenges such as production scheduling, cost-to-serve routing, inventory balancing, and pricing elasticity.
- Create and deploy computer vision solutions for safety, process monitoring, quality control, and automation (e.g., image recognition, object detection, anomaly detection).
- Develop heuristic and machine learning models using Python, BigQuery ML, and Azure services.
- Collaborate with data engineers to ensure reliable and efficient data pipelines from SAP and other enterprise systems.
- Translate business requirements into mathematical models (linear programming, mixed-integer, constraint-based, or stochastic optimization).
- Build and maintain dashboards and decision-support tools.
- Prototype and deploy optimization microservices or AI agents integrated into business workflows.
- Conduct model validation, sensitivity analysis, and post-implementation reviews to measure impact.
- Contribute to the citizen development framework, supporting business users in applying advanced analytics responsibly.
- Document methodologies and communicate insights clearly to technical and non-technical stakeholders.
What we're looking for
- Bachelor’s or Master’s degree in Data Science, Industrial Engineering, Operations Research, Applied Mathematics, or Computer Science.
- Recent graduate or professional with experience in data science, optimization, or AI model development (industry experience preferred).
- Strong proficiency in Python (Pandas, NumPy, SciPy, PuLP, OR-Tools, or Pyomo).
- Experience with SQL/BigQuery and cloud-based data platforms (Azure and Google Cloud preferred).
- Familiarity with SAP datasets or ERP-related data structures is a strong plus.
- Working knowledge of Qlik Sense and Power Platform (Power Automate / Copilot Studio) is desirable.
- Excellent problem-solving and communication skills with the ability to explain complex models to executives and operational teams.
- Willing to travel 25% of the time (~ one week out of the month)
- Must be comfortable with working in both an industrial environment and corporate setting
Tags & focus areas
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