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2 дня назад

TradFi Research Lead

Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
Netherlands/Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
TradFi Research Lead: Leading the development and productionization of systematic mid-frequency trading strategies across traditional financial markets with an accent on alpha generation, portfolio construction, risk modeling, and execution quality. Focus on designing predictive signals, building realistic backtesting and simulation frameworks, mentoring researchers, and improving live strategy performance.

Location: Netherlands or Montreal, Canada

What you will do

  • Lead research and development of systematic trading strategies across equities, futures, ETFs, options, and FX.
  • Generate, validate, and prioritize alpha ideas using statistical, machine learning, and market microstructure techniques.
  • Design predictive signals, portfolio construction models, execution logic, and risk controls.
  • Analyze live performance, transaction costs, slippage, market impact, capacity, turnover, and drawdowns.
  • Define requirements for research infrastructure, data pipelines, simulation frameworks, and production monitoring.
  • Mentor researchers, establish rigorous research standards, and contribute to hiring and the long-term research roadmap.

Requirements

  • Experience leading quantitative research for systematic trading strategies.
  • Strong knowledge of traditional financial markets, including equities, futures, ETFs, options, and FX.
  • Expertise in statistical modeling, machine learning, predictive signals, and market microstructure.
  • Experience with portfolio optimization, capital allocation, risk models, and execution analysis.
  • Ability to collaborate with software engineers on production deployment and research infrastructure.
  • Ability to work from the Netherlands or Montreal, Canada.

Culture & Benefits

  • Research culture focused on scientific rigor, robust validation, and challenging assumptions.
  • Close collaboration between quantitative researchers and software engineers.
  • Opportunity to influence research standards, technology strategy, and the long-term roadmap.

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