Data Scientist | Aspiring AI & ML Engineer
I am a Data Scientist working with real-world data, currently building machine learning solutions at FedEx. My expertise lies in developing predictive models, analyzing complex datasets and creating data-driven solutions supporting business decisions.
My main focus is Machine Learning and modern AI ecosystems, particularly Generative AI, RAG, and LLM-based systems.
- Core Ecosystem:
Python·SQL·Git·Azure DevOps - Machine Learning:
Scikit-learn·XGBoost·LightGBM·Forecasting·Regression·Model Evaluation - Data Engineering:
Azure Databricks·PySpark·Apache Spark·Data Pipelines - Generative AI:
LangChain·LangGraph·RAG·Vector Databases·LLM Applications - Tools:
Docker·Streamlit·FastAPI
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Machine Learning Systems
Building forecasting and predictive solutions using real-world business data. Experienced in model development, feature engineering, hyperparameter tuning, model comparison and generating predictions used in decision-making processes. -
AI & GenAI Engineering
Designing practical AI applications based on Large Language Models, with focus on retrieval systems, RAG architectures and intelligent assistants. -
Data Engineering & Analytics
Working with large-scale data environments using Spark-based technologies. Transforming raw data into reliable analytical workflows and business insights. -
Academic Foundation
MEng Computer Science - Data Science from AGH University of Krakow. Strong background in machine learning, statistics and data analysis.
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📦 FedEx
Working on machine learning solutions supporting logistics forecasting and operational analytics. Building predictive models using XGBoost and LightGBM, processing data with Azure Databricks, and improving model performance through experimentation. -
🤖 AI & LLM Projects
Building end-to-end AI applications combining document processing, semantic search, retrieval pipelines and LLM reasoning workflows. -
🧪 In the Lab
Exploring advanced AI engineering topics including LangGraph, multi-agent systems, production-oriented LLM applications and AI system evaluation.