Trading Systems Developer
Systematic and algorithmic trading · Quant research · AI-assisted engineering
Backtesting · Monte Carlo · Risk systems · Execution diagnostics
Five years of independent quantitative research and applied market study, since February 2021. I build trading research systems that connect market hypotheses, reproducible experiments, risk controls, live MT5 execution and post-trade diagnosis. Alexandria is the fourth system in that progression, and the one I designed, built and operate alone.
Market data
MT5 tick and candle export, live and historical ingestion, gap and conflict checks, feed-freshness monitoring.
Research
Deterministic market-structure rules, reproducible experiments, and systematic parameter exploration.
Simulation
Execution-aware backtesting with explicit fill, no-fill and rejection states, intrabar ordering, broker costs.
Risk
Monte Carlo stress analysis, position sizing, combined exposure, daily and total drawdown limits.
Execution
Broker preflight, MT5 order submission, persisted lifecycle state, restart recovery, end-of-day controls, and post-trade P&L reconciliation against broker truth to the cent.
Operations
REST APIs, health and readiness telemetry, automated daily, weekly and monthly reporting, signal to order to fill diagnostics, and silent-failure detection: the business ledger is cross-checked against an independent process heartbeat, so a channel that is alive but not writing is never reported as a normal day.
Quality
Regression, integration, golden-case and failure-path tests, git-hook automation on every commit, automated deployment through GitHub Actions.
Decision layer
A versioned layer above the chain: it weighs evidence of different quality and publishes what the execution layer is allowed to run. A hybrid decision model, integrating artificial intelligence with code.
Alexandria is proprietary. This page describes the scope of the engineering, not the strategy logic.
Most people who can trade cannot build this. Most people who can build it have never traded.
Since February 2021 I have studied markets and built the tools to test what I found, through four successive systems: roughly 25,000 hours of study, research and engineering. It is the same deliberate method that built a ten-year international music career before it. Alexandria is the fourth: I designed it, built it and operate it alone, and it runs the whole chain above every day. I would rather take longer and build something that keeps running without me.
One search ran 792 million simulated results across ten markets and three years of history, in a single pass, ranked walk-forward and out of sample. Then the survivors go through Monte Carlo stress before anything reaches a live account.
Independent and self-funded, end to end. Every figure on this page can be traced back to the file it came from.
- Based in
- Berlin, Germany
- Status
- Open to roles across Europe
- Looking for
- Quantitative research · Trading platforms · Market data · Backend fintech
- Stack
- JavaScript · TypeScript · Python · Node.js · Express · React · MQL5 / MT5 · Streamlit
- Languages
- Spanish native · English professional · German A2.2, working toward B1
Core expertise
Background
Independent quantitative research and trading-systems development
Berlin. Intensive self-directed market study and applied research, through four successive trading systems. Self-funded throughout.
Trading-strategy training
Seven successive private mentorship programmes in discretionary market-structure trading: liquidity, order flow, session timing and entry-model design. 564 archived sessions, and 15,000+ of those hours in chart study. Those rules were then formalised into deterministic, testable logic, and the ones that did not survive out-of-sample measurement were dropped.
Quant research and algorithm optimisation · Rabot Crypto
Data-driven research for crypto markets. Python dashboards with pandas, NumPy, Dash and Plotly for market behaviour, order-flow context, open interest and key levels. Translated research ideas into testable workflows with developers and traders.
Data Science and Machine Learning bootcamp · SPICED Academy
Berlin. 480+ curriculum hours: Python, pandas, NumPy, scikit-learn, SQL and NoSQL fundamentals, dashboards, deployment concepts.
Music producer, educator and founder
Berlin and international. Built a creative practice and an online education business: production, teaching, mentoring and independent ownership. It is where the discipline of structure, timing and iteration comes from.
The three systems before Alexandria: a configurable multi-timeframe BTC research system in June 2025, a Python and Streamlit application for market-structure and liquidity detection in September, and a React and TypeScript platform with engine comparison and golden-case validation in November.
Looking for someone who has already built the whole thing?
Every figure above is traceable: the run manifest, the git history, the test directory. Ask me for any of them.
