
Wintermute
Posted 18 months ago
Quant Researcher (MFT Focus)
LondonOn-siteFull-time
AI Summary
A quantitative researcher develops and deploys mid-frequency trading strategies for digital assets, builds predictive models, and analyzes high-resolution market data to generate short-term alpha signals for crypto markets.
About this role
About Wintermute
Wintermute is a technology unicorn and one of the largest algorithmic trading companies, specialising in digital assets. We provide liquidity across most cryptocurrency exchanges and trading platforms, a broad range of OTC trading solutions as well as supporting high profile blockchain projects and traditional financial institutions moving into crypto. Wintermute also has a Wintermute Ventures arm that invests in early stage DeFi projects.
Wintermute was founded in 2017 and has successfully navigated industry cycles. Culturally, we combine the best of the two worlds: the technology standards of high-frequency trading firms in traditional markets and the innovative and entrepreneurial culture of technology startups. At Wintermute, we believe in the innovative potential of blockchain, the fundamental innovations, we have a long-term view on the digital asset market and are taking a leadership position in building an innovative and compliant market. You can read more here.
Working at Wintermute
You are an experienced quantitative researcher with existing mid-frequency (MFT) or short-term alpha strategies in traditional finance or crypto markets.
You will leverage Wintermute's sophisticated research, backtesting, and execution infrastructure to adapt and scale your strategies to crypto markets as well as work closely with our quant, trading, and development teams to refine models and explore new opportunities across a range of cryptocurrencies.
Responsibilities:
Hard Skills Requirements:
Nice to have requirements:
Here is why you should join our dynamic team:
Note:
Skills
BacktestingBlockchain DataC++Crypto TradingData AnalysisExchange APIsExecution / Latency OptimizationInterpolationMachine LearningMarket MicrostructureMathematicsParameter OptimisationPerformance ProfilingPythonQuantitative ModelingSimulationStatisticsTime-series
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