27.11.2025 aktualisiert
verifiziert
Premiumkunde
20 % verfügbarSenior Data Consultant | Machine Learning, AI Engineering, MLOps, Data Engineering, Databricks
Zürich, Schweiz
Weltweit
PhD in Theoretical PhysicsSkills
APIsKünstliche IntelligenzComputer VisionMicrosoft AzureBash ShellBig DataClusteranalyseDatenbankenContinuous IntegrationInformation EngineeringDevopsInfrastrukturPythonMachine LearningWindows PowershellRole Based Access ControlAzure Active DirectoryAzure Machine LearningScipyTransformerSoftwareentwicklungSQLSupport Vector MachineSupervised LearningData ScienceAzure Data FactoryPytorchReactJSFlaskLarge Language ModelsRandom ForestPrompt EngineeringApache SparkDeep LearningNaive BayesGenerative AIGitlabGitPandasPytestPysparkScikit-learnHuggingFaceXgboostBicepMachine Learning OperationsGPTDockerUnsupervised LearningDatabricks
AI Engineering
Data Engineering
- Tools
- LangChain
- DSPy
- LangFuse
- OpenAI ChatGPT API
- MCP
- LLamaIndex
- ChromaDB, Weaviate
- Concepts
- Prompt Engineering
- Retrieval Augmented Generation
- Vector Database
- Agent Architectures (ReAct, Chain of Thought)
- LLMOps
- Tools
- Scikit-Learn
- CatBoost
- XGBoost
- SciPy
- SparkML
- Concepts
- Supervised Learning (Random Forest, Boosted Trees, Support Vector Machine, Naive Bayes, K-NN)
- Unsupervised Learning (Dimensionality Reduction: PCA, t-SNE, UMAP,
Clustering: K-Means, DBSCAN, Hierachical Clustering)
- Tools
- PyTorch
- Huggingface
- Concepts
- Autoencoders, RNNs, LSTM, Transformers
- Computer Vision (CNNs)
- Generative AI: Large Language Models (LLM), Prompt Engineering (e.g. with LangChain), Fine Tuning, Parameter Efficient Fine Tuning, Generative Adversarial Networks
Data Engineering
- SQL
- Python Pandas,
- PySpark
- Spark SQL
- Delta Lake
- Databricks
- Azure Data Factory
- Azure Blob Storage
- Azure Machine Learning Studio
- Azure Active Directory
- RBAC
- Databricks
- Infrastructure as Code (ARM, Bicep)
- Python
- PyTest
- Flask
- Fast-API
- Git
- CI/CD
- Gitlab
- Azure DevOps
- Poetry
- PipEnv
- Docker
- Bash
- Powershell
Sprachen
DeutschMutterspracheEnglischverhandlungssicherPortugiesischgutSpanischverhandlungssicher
Projekthistorie
Project roles:
Data Engineer
Tasks:
Lead Data Engineer
Python, PySpark, SQL, Databricks, DeltaLake, Azure DevOps, Azure Data Factory, PowerBI
Data Engineer
Tasks:
Lead Data Engineer
- Development of scalable ETL Pipelines
- technical development of Dashboards and integration of BI use-cases
- Software Development
Python, PySpark, SQL, Databricks, DeltaLake, Azure DevOps, Azure Data Factory, PowerBI
Project roles:
Lead Software Developer and Senior Data Scientist
Tasks:
I developed the software of a ML Pipeline to predict the length of hospital stays.
I have taken the lead in technical and analytical as well as PM tasks.
The technical and analytical tasks included:
Python (Pandas, Scikit-Learn, PyTorch Catboost), SQL, Git and Gitlab, Poetry
Methods:
CatBoost Regression Model, OOP in Python, Scikit-Learn ML Pipelines, Feature Engineering and Selection
Lead Software Developer and Senior Data Scientist
Tasks:
I developed the software of a ML Pipeline to predict the length of hospital stays.
I have taken the lead in technical and analytical as well as PM tasks.
The technical and analytical tasks included:
- Analytical Problem Assessment
- PoC development and evaluation,
- ETL and Data Selection
- ML Software Development in Python
Python (Pandas, Scikit-Learn, PyTorch Catboost), SQL, Git and Gitlab, Poetry
Methods:
CatBoost Regression Model, OOP in Python, Scikit-Learn ML Pipelines, Feature Engineering and Selection
Project roles:
Lead Software Developer and Senior Data Scientist
Tasks:
I developed the software for a ML Software that estimates product recommendations for health insurance products.
I have taken the lead in technical and analytical as well as PM tasks.
The technical and analytical tasks included:
Python (Pandas, Pytest, Scipy), SQL, Git and Gitlab, Poetry, Docker
Methods:
Probabilistical Graphical Models, OOP in Python, Unit-and Integration testing, CI/CD Pipeline
Lead Software Developer and Senior Data Scientist
Tasks:
I developed the software for a ML Software that estimates product recommendations for health insurance products.
I have taken the lead in technical and analytical as well as PM tasks.
The technical and analytical tasks included:
- ETL
- Data Discovery and Selection
- ML Software Development in Python
- Operationalization of the model as a batch process
Python (Pandas, Pytest, Scipy), SQL, Git and Gitlab, Poetry, Docker
Methods:
Probabilistical Graphical Models, OOP in Python, Unit-and Integration testing, CI/CD Pipeline
Zertifikate
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
DeepLearning.AI2019
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
DeepLearning.AI2019
Object oriented programming in Java
Edx2018