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Senior Sports Quantitative Analyst

CompraTica Empleos

EMP:Finance
Tiempo Completo
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Descripción

<div class="content-intro"><p>We are on a mission to pioneer the world’s next era of play.

As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences.

Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.

</p></div><p class="font-claude-response-body break-words whitespace-normal">The Quant team at Super is responsible for developing the models and tools required for trading a wide range of sports, with the aim of providing the best betting experience to current and future customers as the business expands globally.

This means producing prices for the full range of markets, same-game accumulators, 100% betting availability, and 100% cash out.

As a Senior Quant, this role plays a big part in driving that process — bringing industry experience to Player Prop pricing, same-game accumulator contingencies, maximising uptime, and contributing ideas on products and best-in-class modelling methodologies.

</p> <p class="font-claude-response-body break-words whitespace-normal"><strong>What the role involves</strong></p> <ul class="[li_&]:mb-0 [li_&]:mt-1 [li_&]:gap-1 [&:not(:last-child)_ul]:pb-1 [&:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3"> <li class="font-claude-response-body whitespace-normal break-words pl-2">Develop mathematical and statistical models to price core and derivative markets across a range of sports</li> <li class="font-claude-response-body whitespace-normal break-words pl-2">Produce related contingency modelling solutions, including same-game accumulator solutions across multiple sports</li> <li class="font-claude-response-body whitespace-normal break-words pl-2">Provide performance analysis through backtesting and optimising model output</li> <li.

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