Profile
Full Stack Data Scientist with significant experience in Machine/Deep Learning, ML Ops, AI Engineering, Data Engineering, Cloud Data Platforms as well as in Project Management

Tools & Technologies
Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Tensorflow, Keras, Pytorch, scipy, Catboost, XGBoost, nltk, shap, PySpark, Pytest), SQL, Apache Spark, Azure Databricks (Delta Lake, MLFlow, Unity Catalog) Apache Iceberg, Microsoft Azure, Azure DevOps, GitLab, GitHub, Git, Poetry, UV, Claude Code, LangChain, LangGraph, LLamaIndex, DSPy, Langfuse, LangSmith

Key concepts
AI Engineering, Prompt Engineering, Retrieval Augmented Generation, Agentic AI, Machine Learning, Supervised Learning, Decision Trees, Random Forest, Boosted Trees (XGBoost, CatBoost), Support Vector Machine, Naïve Bayes, Bayesian Networks, Logistic & Linear Regression, Deep Learning, Neural Network, Convolutional Neural Networks, Sequence Models, Transformers, Time Series, ARIMA / Unsupervised Learning Clustering, K-Means, DBSCAN, Dimensionality Reduction, PCA, t-SNE / NLP, Large Language Models, Sentiment Analysis, Prompt Engineering, Word/Sentence Embedding / Generative AI, GANs / Topic Modelling, Matrix Factorization, Latent Dirichlet Allocation / Collaborative Filtering / Statistics, Data Mining / Predictive Analytics / Data Engineering, ETL, Data Quality, Data Governance, User Coaching, Customer Coaching, User Training, Customer Training / Project Planning, Project Controlling, Requirements Engineering

Solutions
Big Data Engineering, Data Science, Machine Learning, AI Engineering (LLMs, Agentic AI, Prompt Engineering), MLOps, Explainable AI, Responsible & Ethical AI

Experience

• Data Science & AI Consultant
• PostDoc in Statistical Physics
• PhD in Theoretical Biophysics and Statistical Physics