Quantitative Researcher & Alpha Engineer │ Systematic Trading Strategies │ Python, AI & Institutional Quant Infrastructure

I am a quantitative developer focused on the design, research, and engineering of algorithmic trading systems, operating at the intersection of quantitative modeling, software engineering, and artificial intelligence applied to financial markets.

My experience is centered on building end-to-end quantitative pipelines, covering signal research, feature engineering, statistical validation, robust backtesting, and the implementation of reliable and scalable automated systems. I primarily work with Python, applying machine learning and modern AI techniques only when there is clear statistical justification and measurable operational value.

I am the founder of Titans Invest, where I lead the development of quantitative infrastructure and analytical tools designed for professional environments. The focus is not on isolated strategies, but on system architecture, methodological clarity, reproducibility, and risk control—core principles for both quantitative funds and B2B financial infrastructure products.

Before shifting my focus almost entirely to the Python ecosystem, I accumulated over 14,000 hours of development in Pine Script, working on complex indicators, strategies, and automation projects. This background provided a deep understanding of signal logic, market behavior, and the practical limitations of backtesting—insight that now supports more robust technical decisions in institutional quantitative environments.

I am currently focused on:

• Quantitative systems in Python.
• Algorithmic infrastructure and research frameworks.
• AI applications for research, modeling, and automation.
• Design of scalable quantitative tools (B2B).

My work is guided by technical rigor, structural simplicity, and statistical validation, deliberately avoiding unjustified complexity and fragile solutions.

Work Terms

I am a Quantitative Developer and Algorithmic Trading Specialist, focused on designing, validating, and deploying institutional-grade quantitative trading systems.
My background combines hands-on experience as a trader with 10,000+ hours dedicated to strategy development, market logic, and trading system engineering, initially built in Pine Script and, in recent years, fully applied to Python-based quantitative trading.
I specialize in developing Python quantitative trading systems, covering the entire strategy lifecycle — from data ingestion and signal generation to statistical validation, automation, and production-grade execution.
Core Expertise
• Quantitative strategy development (systematic and factor-based)
• Python for quantitative research and algorithmic trading
• Machine Learning applied to financial markets
• Statistical modeling, validation, and robustness testing
• Professional backtesting frameworks
• Automated execution and high-reliability architectures
• Data pipelines, APIs, WebSockets, and FIX integration
What I Build
• End-to-end quantitative trading systems
• Multi-factor models and statistical regressions
• ML- and AI-driven strategies and optimization pipelines
• Institutional backtests (Out-of-Sample, Walk-Forward, Monte Carlo)
• Automated execution engines with integrated risk controls
• Quantitative research frameworks for systematic strategy discovery
Platforms & Environments
• QuantConnect
• Interactive Brokers
• MetaTrader 5
• NinjaTrader
• TradeStation
• Freqtrade
• Global and crypto brokers
Professional Standards
My work follows institutional best practices, with strict focus on:
• Statistical validity
• Robustness and overfitting control
• Reproducibility
• Scalability
• Clean, maintainable architecture
I do not deliver generic strategies, curve-fitted models, or retail-grade systems.
I build production-ready quantitative infrastructure designed for real capital deployment.
If you are looking for an experienced quantitative developer

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