pythonrisk managementmatlabtime series analysisbacktestingquantitative researchfreelancehedgingsystematic trading
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Зарплата и рынок
Выше рынка
350к-500к ₽/мес
300к ₽350к ₽медиана380к ₽
По похожим ролям (22) ~ 350к ₽/мес
На международном рынке: $155к/год ($98к - $198к)
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Оплачиваемый исследовательский проект с понятными рамками может стать ступенью к постоянной роли, но зарплата ниже бенчмарка платформы, а продолжение сотрудничества не гарантировано.
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Ниже бенчмаркаПонятные задачиОплачиваемое заданиеСовременный стекВозможность продолжения
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Описание вакансии
Текст:
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TL;DR
Paid Research Engagement — Systematic Trading (Quantitative Research): Developing and validating systematic trading strategies across FX, futures, and options with an accent on hypothesis generation, robust backtesting, position management, hedging, and real execution constraints. Focus on distinguishing genuine trading effects from optimization artefacts, preventing overfitting and look-ahead bias, and assessing risk, costs, slippage, and live-trading viability.
Location: Worldwide; fully remote
Salary: 350,000–500,000 RUB/month net
Company
Restadviser operates a systematic trading team managing $40M in assets under management across FX, futures, and options markets.
What you will do
Generate, prioritize, and test systematic trading hypotheses from partially defined research problems.
Design trading logic, including position management, hedging, exposure, and risk controls.
Conduct end-to-end quantitative research from hypothesis generation through robust backtesting and validation.
Account for Bid/Ask execution, transaction costs, slippage, and real-trading constraints.
Analyze statistical, mathematical, or ML-based evidence and distinguish genuine effects from optimization artefacts.
Produce reproducible final backtest code without dependence on third-party trading platforms.
Requirements
Independent experience generating and testing trading hypotheses and researching strategies or signals.
Strong understanding of backtesting, walk-forward analysis, overfitting, and look-ahead bias.
Knowledge of position sizing, exposure and risk management, PnL, and drawdown analysis.
Experience with statistics or time-series analysis and the ability to conduct research independently.
Python, MATLAB, or a comparable programming language by prior agreement.
Must be able to complete a self-contained paid research assignment of up to approximately 40 hours.
Nice to have
Personally originated trading ideas or material contributions to live strategies.
Strategies or signals that reached live trading with real capital.
Experience with FX, futures, tick data, and Bid/Ask execution.
Experience designing position-management or hedging systems.
Experience investigating live degradation or divergence between live and backtested results.
Culture & Benefits
Paid external research engagement; payment is provided regardless of whether the research result is positive or negative.
Additional bonus for reaching predefined target criteria.
Flexible, self-paced scope of up to approximately 40 hours alongside an existing primary commitment.
Potential path to an ongoing research-team role with transparent PnL sharing.
No crypto or HFT activity; proprietary details can remain covered by NDAs.
Hiring process
Complete a paid, self-contained quantitative research assignment.
Strong results and mutual interest may lead to an ongoing role in the research team.
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