Data Analytics AI Engineer at Fireblocks Inc. answer
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Job Description
<div class="content-intro"><p>The world of digital assets is accelerating in speed, magnitude, and complexity, opening the door to new ways for leveraging the blockchain. Fireblocks’ platform and network provide the simplest and most secure way for companies to work with digital assets and it trusted by some of the largest financial institutions, banks, globally-recognized brands, and Web3 companies in the world, including BNY Mellon, BNP Paribas, ANZ Bank, Revolut, and thousands more.&nbsp;</p></div><h4 class="text-text-100 mt-2 -mb-1 text-base font-bold">About the Team</h4>
<p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Join our global Data team, which partners closely with Product, Engineering, and GTM stakeholders to power data-driven decision making and AI-driven products across Fireblocks. The team has evolved from providing deep analysis to becoming enablers, bringing the right data and AI tools so that Sales, Marketing, and Customer Operations can run analysis and forecasting. We operate in a fast-paced, high-growth environment where much of what we build is new, and we figure things out as we go.</p>
<h4 class="text-text-100 mt-2 -mb-1 text-base font-bold">What You'll Do</h4>
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<li class="font-claude-response-body whitespace-normal break-words pl-2">Design and build LLM-powered systems and data agents that directly improve internal capabilities, enabling GTM, Product, and Engineering teams to make faster, smarter, data-driven decisions at scale.</li>
<li class="font-claude-response-body whitespace-normal break-words pl-2">Analyze large-scale datasets to surface strategic insights across the customer lifecycle and revenue funnel; define and track critical KPIs; and translate findings into actionable product and business recommendations.</li>
<li class="font-claude-response-body whitespace-normal break-words pl-2">Evaluate and quantify the business impact of AI initiatives through rigorous experimentation, benchmarking, and model evaluation to continuously optimize LLM performance.</li>
<li class="font-claude-response-body whitespace-normal break-words pl-2">Continuously monitor, refine, and evolve AI models and solutions, iterating on prompt engineering and deployment practices to keep pace with rapidly advancing capabilities.</li>
<li class="font-claude-response-body whitespace-normal break-words pl-2">Ship and maintain production-grade analytics and AI applications through modern CI/CD pipelines (GitLab/GitHub), ensuring reliable, repeatable, and observable deployments.</li>
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