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Queueco
Internship: DeFi Quantitative Trading
8 months ago | 960 views | 4 applications

Internship: DeFi Quantitative Trading

Internship
London

About the company

Queueco is a proprietary trading firm that engages in both conventional as well as cutting-edge alternative markets. Our strategies run 24/7 without manual intervention powered by low-latency infrastructure and the latest machine learning techniques. We're a meritocratic and lean team of highly-motivated scientists and developers and as such value technical ability more than politics: what matters is how good your code is, not how well you sell yourself. We spend no time dealing with clients, customers or investors and instead focus on growing our business by building better technology.

Job Summary

You will be supporting our quantitative researchers in the following areas:

📍Researching vast amounts of De-Fi market data to identify patterns and express your own fully algorithmic trading strategies 📍Creating and implementing De-Fi strategies into production which means direct feedback on your work 📍Manage your portfolio of live strategies and adjust based on market conditions and upcoming economic calendar 📍Generating novel ways of analysing and interpreting our proprietary data 📍Improving the quality of our simulations and accuracy of forecasts 📍Shaping our trading footprint by identifying new markets to trade on

Requirements

📍Qualities that make you an ideal candidate may include: 📍Proficient in one or more of Python/C++/Java with a good foundation in software engineering principles 📍Familiarity with Blockchain technology is a plus 📍Complex problem solving, focusing on results rather than process 📍Unconventional thinking, creativity and persistence 📍Good mix of engineering and data science skills in the domain of time series analysis 📍Ability to build whole data analysis pipelines from data preparation and feature selection to efficient training, hyper-parameter optimisation, validation and testing 📍PhD, MSc from top tier universities in relevant STEM subjects (mathematics, physics, computer science)

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