Quantative Analyst

Finbourne Technology

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Full-time

Legal agreement: Employment

Compensation

GBP100k - 120k/year

~USD134k - 161k/year

Hybrid (United Kingdom)

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Posted over 5 years ago

• Efficiently storing data is not an end but the means to using it. Efficiently pricing, calculating risk and analysing behaviour of large portfolios of instruments is the basis of our day to day work. Orchestrating the interaction of bitemporal databases, multiple pricing libraries and distributed systems using a common API is one of the great data problems in finance with the potential to revolutionise the industry. We hope you’re as excited about it as we are! • We are building LUSID to support thousands of concurrent users, with demanding performance and scalability requirements. This necessitates a focus on quality and automation; do it once, correctly. The analytics team are focused on the pricing and risk aspects of this; developing the architecture, integrating with external analytics and optimizing the throughput of the system.

About Finbourne Technology:

FINBOURNE Technology was founded in 2016 with the mission to reduce the cost of investing and increase transparency for everyone. We’re doing this by changing the way the world manages investment data with LUSID, our open cloud-based investment data platform and marketplace. LUSID is for everyone in the asset management industry from start-up fund managers to global investment institutions. Seven of us started on this journey and we have now grown to more than 70 people. We’ve taken best practice from the B2C technology world and applied this to a B2B technology world currently stuck on old legacy systems with limitations and lengthy implementation periods. What this means is that LUSID is open, API first and developer friendly – a true first for the asset management industry. You can see what our team is busy building – we’ve published APIs for all functions publicly, and released Software Development Kits for developers in four languages (C#, Java, Javascript, Python) on Github.

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