02.09.2026 aktualisiert
100 % verfügbar
Senior AI/Machine Learning and Data Science Engineer
Zürich, Schweiz
Weltweit
PhD Computational Science, MSc Computer Science, ETH ZurichSkills
Künstliche IntelligenzAnalyse von FinanzdatenKünstliche Neurale NetzwerkeFinanzprognoseComputersimulationDatenvisualisierungEmbedded SystemsAktienfondsForecastingMachine LearningDistributed SimulationMilitärische ErfahrungHigh Performance ComputingData ScienceDeep Learning
Data-Driven Intelligence: Precision Engineering
I provide advanced consulting and project management in data science, AI engineering, and time series forecasting. I apply deep theoretical and practical expertise, supporting clients across the entire intelligent systems lifecycle—from exploratory research and prototyping to scalable deployment and continuous optimization.
- Machine Learning & AI Engineering: I develop and integrate predictive models, embedding-based semantic search, and LLM-driven agentic systems. My focus is on robustness, interpretability, and alignment with real-world constraints.
- Time Series Forecasting: I design forecasting pipelines using probabilistic models, deep learning, and hybrid statistical techniques. Solutions are tailored for high-dimensional financial, sensor, environmental, and operational data.
- Data Infrastructure & Hosting: I build custom infrastructure for AI system development and integration. Solutions include containerized microservices in a multi-GPU environment, object storage, and metric-aware observability. I operate an on-prem Kubernetes cluster (300+ cores) and maintain a dedicated hardware lab for full project lifecycle support, from experimentation to production hosting.
- Scientific Research & Technical Consulting: I support research-intensive projects via algorithm design, model evaluation, and reproducible experimentation. My consulting bridges academic rigor with production-grade deliverables.
- Programming & System Design: I implement data pipelines and backend systems in Python, focusing on modularity, I/O performance, and long-term maintainability.
I'm Christian Gloor, a machine learning and data science engineer with two decades of experience building intelligent systems under real-world constraints. Through Christian Gloor Computational Science, I offer 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, I combine academic rigor with deep practical expertise. My experience includes leading R&D at quantitative hedge funds, contributing to mission-critical military software, designing national stock exchange infrastructure, and developing tools for autonomous navigation, simulation, and real-time analytics. See my Project History for more details.
I provide advanced consulting and project management in data science, AI engineering, and time series forecasting. I apply deep theoretical and practical expertise, supporting clients across the entire intelligent systems lifecycle—from exploratory research and prototyping to scalable deployment and continuous optimization.
- Machine Learning & AI Engineering: I develop and integrate predictive models, embedding-based semantic search, and LLM-driven agentic systems. My focus is on robustness, interpretability, and alignment with real-world constraints.
- Time Series Forecasting: I design forecasting pipelines using probabilistic models, deep learning, and hybrid statistical techniques. Solutions are tailored for high-dimensional financial, sensor, environmental, and operational data.
- Data Infrastructure & Hosting: I build custom infrastructure for AI system development and integration. Solutions include containerized microservices in a multi-GPU environment, object storage, and metric-aware observability. I operate an on-prem Kubernetes cluster (300+ cores) and maintain a dedicated hardware lab for full project lifecycle support, from experimentation to production hosting.
- Scientific Research & Technical Consulting: I support research-intensive projects via algorithm design, model evaluation, and reproducible experimentation. My consulting bridges academic rigor with production-grade deliverables.
- Programming & System Design: I implement data pipelines and backend systems in Python, focusing on modularity, I/O performance, and long-term maintainability.
I'm Christian Gloor, a machine learning and data science engineer with two decades of experience building intelligent systems under real-world constraints. Through Christian Gloor Computational Science, I offer 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, I combine academic rigor with deep practical expertise. My experience includes leading R&D at quantitative hedge funds, contributing to mission-critical military software, designing national stock exchange infrastructure, and developing tools for autonomous navigation, simulation, and real-time analytics. See my Project History for more details.
Erfahrung
Berufserfahrungmehr als 10 Jahre
Freelancer seit2005
Sprachen
DeutschMutterspracheEnglischverhandlungssicher
Projekthistorie
We built a global macro hedge fund using machine learning strategies. I oversaw the design, development, and operation of the research and trading infrastructure:
* a Python/Jupyter framework for quantitative research with access to an on-premises compute cluster, cloud services, and two data centers,
* over 400 deployed machine learning models, trading automatically on global futures markets.
I introduced machine learning, established the first set of models, and mentored fellow data science researchers.
* a Python/Jupyter framework for quantitative research with access to an on-premises compute cluster, cloud services, and two data centers,
* over 400 deployed machine learning models, trading automatically on global futures markets.
I introduced machine learning, established the first set of models, and mentored fellow data science researchers.
I joined Man Systematic Strategies, a specialized team for developing new models, later merged into AHL. I designed and implemented
* a dynamic volatility gearing overlay to AHL's Core Momentum strategy. Robust Python code in production trading billions,
* a web-based 3D interface for a volatility prediction strategy that used high-frequency data,
* a dynamic Risk Parity strategy that traded across 70 markets,
* new AI trading models as part of the AHL Machine Learning Initiative.
* a dynamic volatility gearing overlay to AHL's Core Momentum strategy. Robust Python code in production trading billions,
* a web-based 3D interface for a volatility prediction strategy that used high-frequency data,
* a dynamic Risk Parity strategy that traded across 70 markets,
* new AI trading models as part of the AHL Machine Learning Initiative.
For a Swiss company supplying the Military. I designed and wrote the software for a reconnaissance vehicle prototype.
- User interface for operating the optical and range-finding instruments.
- Embedded server control software that routes messages between subsystems.
- User interface for operating the optical and range-finding instruments.
- Embedded server control software that routes messages between subsystems.