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David A

David A

Systematic Trader · Applied Data Science Graduate — builder of an end-to-end market data, backtesting & execution stack

Talento
BarcelonaMiembro desde 18 de agosto de 2026
PythonpandasNumPyMassive/Polygon.io APITradingViewPine ScriptSignalStackDAS Trader APIStatisticsMarket microstructureOrder booksShort locates and borrowTrading haltsBacktestingRisk managementPerformance analytics
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PythonpandasNumPyMassive/Polygon.io APITradingView

Sobre mí

Applied Data Science graduate (UOC) with a mathematics foundation (Universitat de Barcelona) and 7 years of hands-on trading experience — the last 2 running a fully systematic, automated intraday strategy on US small-cap equities. Sole designer and builder of the complete infrastructure behind it: market data acquisition and cleaning pipelines, a custom Python backtesting engine, a real-time scanner and an automated execution workflow. Practitioner-level command of market microstructure (order books, liquidity, short locates and borrow, halts) — bringing exactly the trading domain expertise this role requires, and looking to grow it into professional-scale market data platforms.

Experiencia

Independent Systematic Trader — US Small-Cap Equities at Independent (2019-01 – Present)

Self-directed quantitative trading operation. Every component below designed, built and operated single-handedly:

  • Market data pipeline (Python): automated acquisition of historical and intraday data through REST APIs (Massive, formerly Polygon.io), with cleaning, normalization, filtering and gap handling to maintain a research-ready dataset covering thousands of small-cap tickers.
  • Custom backtesting engine: intraday simulation with realistic execution assumptions — slippage, commissions, borrow/locate costs — position sizing, and full performance analytics (Sharpe, Calmar, R-multiples, MAE/MFE, drawdown profiles); designed to preserve point-in-time correctness and avoid look-ahead bias.
  • Real-time market scanner (Python): live screening of API data to detect intraday candidates through float, volume, price-action and volatility filters.
  • Execution automation: signal generation in Pine Script (TradingView) routed through webhooks (SignalStack) to broker order execution; automated short-locate workflow through the DAS Trader API.
  • Domain expertise: small-cap microstructure — L2 order flow, float dynamics, trading halts, locate availability and borrow costs; live trading under strict rule-based risk management.

Private Mathematics Tutor at Private (2020-01 – Present)

Individual and small-group classes for secondary, baccalaureate and university-entrance students — daily practice turning complex quantitative ideas into clear explanations.

Earlier roles at Saint-Gobain Sekurit, Vins Font, Hospitality and Leisure (2014-01 – 2025-01)

Process and quality control in manufacturing (Saint-Gobain Sekurit — laminated-glass tempering furnace, process parameters and QA) and wine production (Vins Font — filtration control and parameter logging); customer-facing roles in hospitality and leisure.

Educación

BSc in Applied Data Science – Universitat Oberta de Catalunya (UOC) (2026-01)

Mathematics Degree in Mathematics – Universitat de Barcelona (2011-01 – 2013-01)

Habilidades

Systematic TraderApplied Data Science Graduatebuilder of an end-to-end market databacktesting & execution stack

Valoraciones

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