Quantitive Researcher (Crypto Markets)
⚲ Amsterdam / Montreal
About the Role
Own the full lifecycle of medium-frequency systematic trading strategies for digital-asset markets, with holding periods ranging from seconds to days—from idea generation and validation to implementation and live monitoring across spot and derivatives.
Research alpha across order books, trades, funding, basis, and liquidations.
Build realistic backtests that account for fees, slippage, latency, liquidity, and market impact.
Validate strategies out of sample, across market regimes, and with controls for data leakage and overfitting.
Evaluate strategies by risk-adjusted returns, decay, turnover, capacity, and execution sensitivity.
Combine signals into portfolios and define risk, sizing, and execution rules.
Implement production-quality strategy and execution logic.
Monitor live performance and adapt strategies as market structure changes.
Automate research workflows and collaborate with engineering on production deployment.
About the Team
We are building a research lab first — and a proprietary investment fund around it. The core belief is that long-term trading edge comes from a systematic ability to generate, test, and compound research insights faster and more rigorously than the market.
The goal is to remove legacy constraints and rethink financial market forecasting using modern systems, new hardware paradigms, and frontier AI. The goal is to tightly integrate execution, research, and infrastructure into a single coherent system.
You might thrive in this role if you have
2+ years building systematic trading strategies, with experience taking research from hypothesis to live deployment.
Strong knowledge of crypto market structure, including centralized exchanges, spot, perpetuals, and funding mechanics.
Solid foundation in probability, statistics, optimization, and time-series analysis.
Strong proficiency in machine learning and deep learning, including robust model development and validation on noisy, non-stationary time-series data.
Strong Python skills and the ability to write reliable, production-quality code.
Experience with large market datasets, exchange APIs, and live trading systems.
Nice to Have
Experience with DEX market structure and execution, including AMMs, on-chain data, gas costs, MEV, and fragmented liquidity.
Experience with high-frequency trading, low-latency systems, or market-making strategies.
Quantitive Researcher (Crypto Markets)
⚲ Amsterdam / Montreal
About the Role
Own the full lifecycle of medium-frequency systematic trading strategies for digital-asset markets, with holding periods ranging from seconds to days—from idea generation and validation to implementation and live monitoring across spot and derivatives.
Research alpha across order books, trades, funding, basis, and liquidations.
Build realistic backtests that account for fees, slippage, latency, liquidity, and market impact.
Validate strategies out of sample, across market regimes, and with controls for data leakage and overfitting.
Evaluate strategies by risk-adjusted returns, decay, turnover, capacity, and execution sensitivity.
Combine signals into portfolios and define risk, sizing, and execution rules.
Implement production-quality strategy and execution logic.
Monitor live performance and adapt strategies as market structure changes.
Automate research workflows and collaborate with engineering on production deployment.
About the Team
We are building a research lab first — and a proprietary investment fund around it. The core belief is that long-term trading edge comes from a systematic ability to generate, test, and compound research insights faster and more rigorously than the market.
The goal is to remove legacy constraints and rethink financial market forecasting using modern systems, new hardware paradigms, and frontier AI. The goal is to tightly integrate execution, research, and infrastructure into a single coherent system.
You might thrive in this role if you have
2+ years building systematic trading strategies, with experience taking research from hypothesis to live deployment.
Strong knowledge of crypto market structure, including centralized exchanges, spot, perpetuals, and funding mechanics.
Solid foundation in probability, statistics, optimization, and time-series analysis.
Strong proficiency in machine learning and deep learning, including robust model development and validation on noisy, non-stationary time-series data.
Strong Python skills and the ability to write reliable, production-quality code.
Experience with large market datasets, exchange APIs, and live trading systems.
Nice to Have
Experience with DEX market structure and execution, including AMMs, on-chain data, gas costs, MEV, and fragmented liquidity.
Experience with high-frequency trading, low-latency systems, or market-making strategies.
Quantitive Researcher (Crypto Markets)
⚲ Amsterdam / Montreal
About the Role
Own the full lifecycle of medium-frequency systematic trading strategies for digital-asset markets, with holding periods ranging from seconds to days—from idea generation and validation to implementation and live monitoring across spot and derivatives.
Research alpha across order books, trades, funding, basis, and liquidations.
Build realistic backtests that account for fees, slippage, latency, liquidity, and market impact.
Validate strategies out of sample, across market regimes, and with controls for data leakage and overfitting.
Evaluate strategies by risk-adjusted returns, decay, turnover, capacity, and execution sensitivity.
Combine signals into portfolios and define risk, sizing, and execution rules.
Implement production-quality strategy and execution logic.
Monitor live performance and adapt strategies as market structure changes.
Automate research workflows and collaborate with engineering on production deployment.
About the Team
We are building a research lab first — and a proprietary investment fund around it. The core belief is that long-term trading edge comes from a systematic ability to generate, test, and compound research insights faster and more rigorously than the market.
The goal is to remove legacy constraints and rethink financial market forecasting using modern systems, new hardware paradigms, and frontier AI. The goal is to tightly integrate execution, research, and infrastructure into a single coherent system.
You might thrive in this role if you have
2+ years building systematic trading strategies, with experience taking research from hypothesis to live deployment.
Strong knowledge of crypto market structure, including centralized exchanges, spot, perpetuals, and funding mechanics.
Solid foundation in probability, statistics, optimization, and time-series analysis.
Strong proficiency in machine learning and deep learning, including robust model development and validation on noisy, non-stationary time-series data.
Strong Python skills and the ability to write reliable, production-quality code.
Experience with large market datasets, exchange APIs, and live trading systems.
Nice to Have
Experience with DEX market structure and execution, including AMMs, on-chain data, gas costs, MEV, and fragmented liquidity.
Experience with high-frequency trading, low-latency systems, or market-making strategies.
