Precision Engineering for Data-Driven Intelligence
Christian Gloor Computational Science delivers advanced consulting in data science, AI engineering, and time series forecasting. We use deep theoretical understanding and practical implementation expertise to support clients across the entire lifecycle of intelligent systems, from exploratory research and prototyping to scalable deployment and continuous optimization.
Machine Learning & AI EngineeringDevelopment and integration of predictive models, embedding-based semantic search, and LLM-driven systems. Emphasis on robustness, interpretability, and alignment with real-world constraints.
Time Series ForecastingDesign of forecasting pipelines using probabilistic models, deep learning architectures, and hybrid statistical techniques. Tailored for high-dimensional financial and sensor data, environmental signals, and operational metrics.
Data Infrastructure & HostingCustom infrastructure for developmet and integration of AI systems. Solutions include containerized microservices in a multi-GPU environment, object storage, and metric-aware observability. We operate an on-prem Kubernetes cluster with over 300 cores and maintain a dedicated hardware lab. This enables us to support clients through the full project lifecycle - from early experimentation and prototyping to production deployment and scalable hosting.
Scientific Research & Technical ConsultingSupport for research-intensive projects through algorithm design, model evaluation, and reproducible experimentation. Collaborative consulting that bridges academic rigor with production-grade deliverables.
Programming & System DesignImplementation of data pipelines and backend systems in Python, with focus on modularity, I/O performance, and long-term maintainability.
About Christian Gloor
Christian Gloor is a machine learning and data science engineer with two decades of experience building intelligent systems that operate under real-world constraints. Through Christian Gloor Computational Science, he offers consulting, coaching, development, and infrastructure services focused on machine learning, time series forecasting, and data-centric AI engineering.
With a PhD in Distributed Computing from ETH Zurich, Christian combines academic rigor with deep practical expertise. He has led research and development efforts at quantitative hedge funds, contributed to mission-critical software for military systems, designed exchange infrastructure for a national stock exchange, and developed tools for autonomous navigation, simulation, and real-time analytics. See Project History for more details.
Contact
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