Avaron AB is seeking an Optimization Data Scientist to develop and deploy production-grade optimization models in a data-rich environment where analytics directly informs business decisions. The role combines discrete optimization, machine learning, data engineering, and stakeholder collaboration to improve how complex decisions are modeled, deployed, and monitored in practice. You will help develop, maintain, and scale an existing optimization solution while strengthening the surrounding data and MLOps setup, covering the full lifecycle from data wrangling and model improvement to cloud deployment, monitoring, and communicating results. You will collaborate closely with Data Scientists, ML Engineers, and Product Managers in an Agile environment. This is an excellent opportunity to turn advanced analytics into reliable production solutions. Responsibilities include maintaining and improving the optimization model by identifying weaknesses and implementing concrete enhancements; presenting model outputs and analytical findings to stakeholders; monitoring and maintaining the deployed AI product on Google Cloud Platform to ensure robustness, efficiency, and stability in production; improving data preparation and wrangling pipelines and integrating additional data sources to strengthen model inputs; collaborating with cross-functional teams to improve performance, reliability, and scalability; applying MLOps practices for deployment, monitoring, and lifecycle management of machine learning models; performing ad hoc analyses and creating visualizations to support data-driven dec

Avaron AB is seeking an Optimization Data Scientist to develop and deploy production-grade optimization models in a data-rich environment where analytics directly informs business decisions. The role combines discrete optimization, machine learning, data engineering, and stakeholder collaboration to improve how complex decisions are modeled, deployed, and monitored in practice. You will help develop, maintain, and scale an existing optimization solution while strengthening the surrounding data and MLOps setup, covering the full lifecycle from data wrangling and model improvement to cloud deployment, monitoring, and communicating results. You will collaborate closely with Data Scientists, ML Engineers, and Product Managers in an Agile environment. This is an excellent opportunity to turn advanced analytics into reliable production solutions. Responsibilities include maintaining and improving the optimization model by identifying weaknesses and implementing concrete enhancements; presenting model outputs and analytical findings to stakeholders; monitoring and maintaining the deployed AI product on Google Cloud Platform to ensure robustness, efficiency, and stability in production; improving data preparation and wrangling pipelines and integrating additional data sources to strengthen model inputs; collaborating with cross-functional teams to improve performance, reliability, and scalability; applying MLOps practices for deployment, monitoring, and lifecycle management of machine learning models; performing ad hoc analyses and creating visualizations to support data-driven dec