About the Role
* Develop and implement advanced optimization models using PaCo algorithms for solving complex integer and mixed-variable problems with multiple objectives and business constraints.
* Create and benchmark various machine learning models based on NSGA-II/III MOEA/D Simulated Annealing CP-SAT and Mixed-Integer Linear Programming MILP.
* Design composite objective functions and lexicographic hierarchies to prioritize key performance indicators such as logistics cost service level and profit margin.
* Generate accurate short- and mid-term demand forecasts using regression ensembles neural networks and time series techniques, and integrate these forecasts into optimization models.
* Built automated pipelines for training inference and optimization ensuring traceability versioning and performance using Python PySpark MLflow Docker and GitHub Actions.
* Execute and monitor experiments in cloud-based distributed environments Azure Databricks optimizing both computational performance and cost.
* Collaborate with cross-functional teams to align business goals validate results and ensure the impact of deployed solutions.