End-to-End Car Price Predictor
A complete data & ML pipeline: From raw web data to a production-ready prediction model.
Problem & Goal
Problem: How to analyze the Czech used-car market, detect underpriced listings, and accurately predict a car's price without access to official APIs from major car portals?
Goal: Build a robust, fully automated system capable of legally scraping dynamic websites, cleaning raw data, storing it in a structured database, and training an accurate machine learning model on top of it.
Data Sourcing & Scraping
Extract
- ▸ Async Python scraper with parallel data collection
- ▸ User-Agent rotation, smart throttling
- ▸ HTML parsing + hidden JSON schema extraction
ETL Pipeline & Data Cleaning
Transform · Load
- ▸ Pandas/NumPy pipeline - duplicates, missing values, outliers
- ▸ Text-to-numeric parsing for messy string fields
- ▸ Feature engineering: equipment, location, body type
Modelling & Machine Learning
Model
- ▸ EDA + regression models (Scikit-learn / XGBoost)
- ▸ Hyperparameter tuning & cross-validation
- ▸ Underpriced listing detection
Experience & Projects
Commercial internships on real products and independent open-source development.
Software Engineer
May 2024 – September 2024
- ▸ Full design & implementation of Front-End and Back-End (API logic) for a public website and internal management dashboard - LinkTV project
- ▸ Server-side logic in Node.js, MongoDB database work
- ▸ Application infrastructure management on AWS
Software Engineer
January 2023 – May 2024
- ▸ Development of a real-time video production platform and SPA dashboards for live stream management
- ▸ Serverless backend design on AWS and system plugins for Elgato Stream Deck
- ▸ Linux, Node.js, AWS cloud services
Personal Projects
2023 – Present
- ▸ Car Price Assistant: Chrome extension + FastAPI Python backend - shows price fairness directly inside car listings
- ▸ Chess Dashboard: Full-stack analytics app (Next.js / TypeScript) - visualises game data from Chess.com and Lichess
- ▸ Full project lifecycle: problem analysis → architecture → clean code → published on GitHub
Studies
Czech Technical University in Prague
Faculty of Information Technology (FIT)
FIT CTU is consistently ranked as the top IT faculty in the Czech Republic.
Key subjects
- Algorithms & graph theory
- Programming & OOP
- Operating systems
- Linux
- Database systems & SQL
- Big Data & NoSQL
- Machine learning & neural networks
- Data visualization
- DevOps & CI/CD
- Cryptography & security
Who I am
I'm a 21-year-old Artificial Intelligence student at FIT CTU Prague. Alongside my studies, I have 2+ years of commercial experience as a Software Engineer - working on real-time platforms, AWS cloud infrastructure, and internal dashboards.
I'm currently transitioning into Data Engineering and applied Machine Learning. I enjoy building things from scratch - from data collection through ETL pipelines to deploying models in production. I work independently, learn fast, and ship.
21 years old, Prague / Bratislava
BSc. AI - FIT CTU Prague
2+ years commercial experience
Open to internships from June 2026
What I work with
Technologies grouped by how I think about them as an engineer.
Core & Algorithms
Data & Machine Learning
Backend & Cloud
Frontend & Tools
Availability & Contact
June – September 2026
Full-time · 40 hrs/weekIdeal for intensive onboarding, covering summer holidays in your team, or jumping into an ongoing project.
From October 2026
Part-time · 120+ hrs/monthFully flexible schedule adapted to working alongside the winter semester.
Looking for someone in Prague who doesn't just write code blindly, but understands data and knows how to ship things? Write to me. I'd be happy to share my screen on a quick 10-minute call and walk you through my project architecture live.