🎓 MSc in Data and Web Science – Aristotle University of Thessaloniki

💼 Data Scientist | AI Engineer | Generative AI

🤖 Experienced in Machine Learning, Demand Forecasting, NLP, LLM Applications, RAG, and Production AI Systems

📍 Based in Thessaloniki, Greece

📬 gregorybarbas@gmail.com | LinkedIn | GitHub

I’m a Senior Data Scientist / AI Engineer with 4+ years of experience developing machine learning, predictive analytics, demand forecasting, NLP, and Generative AI solutions.

My work focuses on designing and delivering end-to-end AI systems — from data preparation, feature engineering, model development, validation, and backtesting, to API-based deployment and production workflows.

I have hands-on experience with:

• Statistical forecasting and time-series analysis
• Machine learning and ensemble modeling
• Demand forecasting for retail and supply chain optimization
• Large Language Model applications
• Retrieval-Augmented Generation systems
• Semantic search and vector databases
• Agentic AI workflows and AI assistants
• FastAPI-based AI services and cloud-native deployments

I’m especially interested in building practical AI systems that combine machine learning, NLP, LLMs, and scalable engineering to solve real-world problems.

I design and deploy AI applications using tools such as OpenAI APIs, LangChain, FastAPI, embeddings, vector databases, and Retrieval-Augmented Generation.

My recent work includes:

• Building RAG systems for document understanding and information retrieval
• Developing AI assistants for document processing and decision support
• Implementing semantic search pipelines using embeddings and vector databases
• Designing agentic workflows for complex information retrieval tasks
• Evaluating LLM performance through prompt optimization, structured testing, and retrieval quality metrics

I have strong experience in developing forecasting and predictive analytics solutions for large-scale retail and supply chain datasets.

This includes:

• Demand forecasting for product-store combinations
• Time-series modeling and statistical forecasting
• Feature engineering for predictive models
• Ensemble learning using models such as XGBoost and LightGBM
• Model validation, backtesting, error analysis, and monitoring
• Automated pipelines for training, evaluation, forecasting, and reporting

Developed a dataset and evaluated transformer-based models for generating plain-language summaries of clinical trial outcomes, aiming to make medical information more accessible to the public.

Tech: NLP, Transformers, DistilBERT, Mistral-7B, Summarization, Evaluation → Check out the repo

A project focused on using Large Language Models to generate concise summaries of financial and news articles, with tools for evaluation, visualization, and interactive exploration.

Tech: LLMs, NLP, Summarization, Evaluation, Visualization → Check out the repo

A demand forecasting challenge solution involving the prediction of daily probabilistic demand distributions for item-store combinations.

Tech: Time Series, Forecasting, Machine Learning, Probabilistic Modeling, Retail Demand → Check out the repo

• Languages: Python, SQL, Java, C++
• Data Science: Pandas, NumPy, scikit-learn, statistical modeling
• Machine Learning: XGBoost, LightGBM, ensemble learning, feature engineering
• Forecasting: Time-series analysis, statistical forecasting, backtesting, error analysis

• Frameworks: PyTorch, TensorFlow, Hugging Face Transformers
• NLP: Text classification, summarization, information extraction, semantic retrieval
• LLMs: OpenAI API, prompt engineering, LLM evaluation, LLM-powered applications

• RAG: Retrieval-Augmented Generation, embeddings, semantic search
• Frameworks: LangChain, MCP, agentic AI workflows
• Vector Search: Vector databases, embedding-based retrieval

• APIs: FastAPI
• Databases: SQL, MongoDB, vector databases
• Cloud & DevOps: AWS, Docker, Kubernetes, CI/CD
• Tools: Git, Linux, Jupyter, Streamlit

• MSc in Data and Web Science Aristotle University of Thessaloniki

• BSc in Computer Science Aristotle University of Thessaloniki

• Erasmus+ Computer Science Mälardalen University

• Greek — Native
• English — C2 Proficiency

🤖 Building production-ready AI and LLM applications

🔎 Exploring RAG, semantic search, and agentic AI systems

📊 Improving forecasting and predictive analytics workflows

📢 Sharing more practical ML, NLP, and Generative AI projects on GitHub

Thanks for visiting! 🚀