Senior Quantitative Researcher

1 week ago

Oxford, Oxfordshire, United Kingdom Fasanara Capital Full time
Founded in 2011, Fasanara Capital is a London-headquartered FCA-authorised investment firm and technology platform. Fasanara manages c. USD 4 billion in Fintech strategies on behalf of pension funds and insurance companies in Europe and North America, and a mandate from the European Investment Fund (EIF).

With over 200 employees across five offices, Fasanara is a pioneer investor in Fintech Lending through its liquid Alternative Credit funds, enabling Real Economy Impact.

Powered by its technology platform with 136 fintech lenders fully integrated from over 60 countries, Fasanara manages the largest and longest standing Fintech Lending fund in Europe.

Additionally, Fasanara invests in early-stage Fintech companies via its venture capital vehicles, using its central role in the Fintech ecosystem to identify and back revolutionary new businesses.

Our Culture

We are strong believers in meritocracy, and we seek to reward people based on impact and excellence. There is no bureaucracy, typical of large organisations. The environment is collaborative, entrepreneurial, and trust based. We set ambitious goals, work extremely hard, stress teamwork, and adhere to the highest level of excellence in everything we do. We are only as good as our team. Thus, we are building the firm around exceptional talent.

The role

We are looking for a Senior Quantitative Researcher specialising in high-frequency trading. Leveraging your expertise in statistical modelling and quantitative analysis of our trading, you will play a key role in leading our short-term alpha research and seeking to improve our low-latency infrastructure.

Responsibilities
Research and development of a framework for short-term alpha signals with horizons ranging from milliseconds to secondsImprovements to existing strategies as well as development and ownership of new ones, namely market makingAnalysing our existing trading and taking ownership of projects to improve latency, quoting logic, slippage etc.5+ years of high frequency trading experience from traditional finance and/or cryptoKnowledge of short-term alpha signals and their implementationKnowledge of low-latency trading systems and their behaviourStrong market-oriented mindset with the desire to conduct thorough scientific researchExperience using quantitative techniques to solve complex data-intensive problems Strong skills in Python, SQL and working knowledge of C++/Java Hands on experience with large volumes of time-series data - primarily in SQL

If you feel you don't necessarily have all of the experiences that we're looking for, but still believe you could be excellent at this role, we'd still be keen to hear from you

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