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Builds and deploys AI/ML models and MLOps pipelines to optimize industrial operations, working with Python and cross-functional teams.
Leads a team to build and maintain VELUX’s global data platform and supports AI initiatives using cloud-based data solutions.
Build and deploy AI/ML models for industrial use cases like predictive maintenance and process optimization, using Python, TensorFlow/PyTorch, and MLOps pipelines.
Leads mechanical design for data-center projects, mentors junior engineers, and shapes technical strategies while collaborating with clients and multidisciplinary teams.
Design and deliver data-driven insights using ML and Python/R to inform business decisions at a climate-tech company.
Engineer and optimize a cloud data warehouse during Ørsted’s migration from Azure to AWS, ensuring reliable data pipelines and influencing cloud architecture decisions.
Build and deploy data-driven solutions using Python, ML, and Azure to optimize building systems and sustainability for Johnson Controls' smart-city and decarbonization products.
Build and optimize cloud data pipelines and warehouses during a major migration from Azure to AWS, ensuring reliable data flow and cost-efficient performance.
Build and evaluate data-driven solutions for smart buildings and climate tech using Python, Azure ML, and SQL; track impact with attribution methods.
Build core cloud data services (DBaaS, Docker Registry, secret management) on Kubernetes, owning the full stack from APIs to production reliability for a European sovereign cloud platform.
Build and optimize Ørsted’s cloud data warehouse, migrating from Azure to AWS while ensuring reliable, scalable data pipelines and platform performance for enterprise analytics.
Maintain and migrate Ørsted’s enterprise data warehouse from Azure to AWS, ensuring scalable, high-performance data pipelines and platform reliability for analytics teams.
Senior role combining data science and software engineering to generate insights and technical communications for smart-building and climate-control systems using Python/R and SQL.
Build and modernize backend services and TB-scale data pipelines in Python/Java to process aviation flight data, optimizing fuel use and CO² emissions for airlines.
Builds and maintains scalable ETL/ELT pipelines and data products for machine data, CRM, and enterprise systems to power analytics and customer insights.
Builds and maintains scalable data pipelines and analytics infrastructure to process IoT and enterprise data for climate-tech solutions.
Design and deploy AI/ML models to optimize global manufacturing operations using Industry 4.0 practices.
Build and maintain scalable data pipelines and MLOps infrastructure for industrial AI solutions in mining, energy, and infrastructure sectors, deploying models in cloud/edge environments.
Build and maintain scalable data pipelines and MLOps workflows for industrial AI solutions in mining, energy, and infrastructure, deploying models in cloud/edge environments.
Build and maintain Arla’s enterprise-grade data platform using Azure Databricks, PySpark, and Terraform to power data-driven decisions across the global dairy supply chain.
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