About

From the warehouse floor to systems that think in data.

My name is Ilko Vasilev and I am from Razgrad, Bulgaria. With the help of AI, I build tools for finance, analysis and automation. They collect data from many places, score it and run on their own. I taught myself through real projects, and I check everything before I call it finished.

  • Based inRazgrad, Bulgaria
  • WorkRemote, or relocation for the right role
  • LanguagesBulgarian (native), English (working proficiency), Russian (basic)

In short

What I bring to a team

I turn a vague question into a working system. I describe what needs to be built, with what data, and how we will know that it works. Then I direct AI as it writes the code, test it on real data and send it back for fixes until the result passes the test.

I am not a classic programmer and I do not pretend to be one. My strength lies elsewhere: I understand the problem, I know what to ask for, and I do not accept a number I cannot verify. That is how I built the four projects in this portfolio, from a sentiment terminal with more than 100 sources to an analysis of 751,500 customer reviews.

Before that I worked in the warehouse of Ozone.bg and as a sales floor supervisor in a supermarket. That is where the habits I still use come from: accuracy under pressure, clear procedures and ownership of the result.


What I do well

Three directions, backed by projects

I

AI and automation

Systems that work without me: they check every few minutes, keep a history in a database, send Telegram alerts and come with a dashboard in the browser or on the phone. The AI models run on an ordinary computer, with no paid services.

  • FinBERT AI model running locally in ONNX
  • 24/7 operation on my own Linux server with HTTPS
  • Windows desktop app (.exe)
  • Alerts and reports with no manual work

Proven in Market Sentiment Terminal and Strategy Terminal

II

Data analysis

Collecting data from many sources, cleaning it and removing duplicate and wrong records, then analysis with a clear conclusion. I check the method against independent labels, and every number in the text is matched automatically against the data.

  • Cleaning and merging large datasets
  • Accuracy checks against human labels
  • Forecasts and formulas built on official statistics
  • Reports with recommendations tied to numbers

Proven in the review analysis and the inventory plan

III

Finance and trading

Since 2023 I have studied the financial markets on my own: technical and fundamental analysis of crypto, forex, stocks, ETFs and futures. I do not judge ideas by eye but with backtests, real fees and a comparison against random entries.

  • TradingView, ATAS (order flow), MetaTrader
  • Backtest on 30 million one-minute candles
  • News sentiment by sector and company
  • Indicators in Pine Script

Proven in Strategy Terminal and Market Sentiment Terminal

The path

How I got here

No university. Everything after high school I learned on the job and through projects.

  1. 2022

    “Ekzarh Yosif” language high school, Razgrad

    English and Russian profile. My English is at working proficiency.

  2. After high school

    Sales floor supervisor, supermarket

    Responsible for the shift, the tills and reconciling daily revenue, restocking, and solving customer issues on the spot.

  3. Next

    Warehouse, Ozone.bg

    Processing orders for a high-volume online store: scanning, tracking stock and checking every parcel.

  4. Since 2023

    Financial markets, self-taught

    Technical and fundamental analysis, consistently and on my own. I wanted to test my ideas with data rather than gut feeling, and that led me to build my own tools.

  5. Today

    Systems built with AI

    A sentiment terminal, a signal system with a backtest, a review analysis and an inventory plan. Four projects that work and have been tested.


Approach

Four rules I work by

  1. 01

    The question first, the tool second

    I start from what needs to be solved and what a good result looks like. The technology comes after that.

  2. 02

    Test against reality

    Backtests with fees, comparisons against chance, human labels, automatic checks of every number. A pretty chart proves nothing.

  3. 03

    Be honest about what does not work

    If something does not beat chance or the data is not enough, I say so. That is how good decisions get made.

  4. 04

    Finished, not a demo

    A working app, a server running 24/7, a report that downloads to Excel. Not a prototype that works only once.

What I can do

Building with AI
I turn an idea into clear requirements, direct AI as it writes the code, test it and ask for fixes until the system works.
Testing
Tests on real data, backtests, comparisons against chance, finding errors and their causes.
Markets
Technical and fundamental analysis of crypto, forex, stocks and futures.
Platforms
TradingView, ATAS, MetaTrader, Excel, Google Sheets.
Languages
Bulgarian (native), English (working proficiency), Russian (basic).

What my projects are built on

Code
Python (pandas, numpy, asyncio), JavaScript, HTML/CSS, Pine Script, SQLite.
AI and data
FinBERT in ONNX, VADER, text processing, statistical checks.
Infrastructure
Linux server (Ubuntu), HTTPS with Caddy, Telegram API, desktop app (.exe).
Data
SEC, Bulgarian National Statistical Institute, Binance, Dukascopy, Yahoo, CoinGecko, Google Play, Trustpilot.

What I am looking for

Work with data, automation or AI.

Data analysis, fintech, AI automation, operations or support. I prefer remote work, and I am ready to relocate for the right role. I would be glad to show my projects live.