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Visa is seeking a Blockchain Technology & Analytics Analyst in San Francisco to evaluate, monitor, and implement blockchain and digital asset technologies. The role blends analytics, AI-assisted prototyping, technical due diligence, and stakeholder storytelling for product and technology teams.
The candidate will prototype PoCs, deploy apps on AWS, and build dashboards to monitor validator performance and network metrics, translating findings for executives and engineers alike.
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
We are looking for a technically curious and highly motivated Blockchain Technology & Analytics Analyst to support the evaluation, monitoring, and implementation of blockchain and digital asset technologies.
This role combines blockchain data analytics, AI-assisted development and research, technical due diligence, and project execution . The ideal candidate is comfortable working hands-on with blockchain data and infrastructure while also being able to translate technical concepts into clear insights and presentations for business, product, technology, and client stakeholders.
The candidate does not need to be a blockchain expert on day one, but should have a strong technical foundation, curiosity about emerging technologies, and the ability to rapidly learn new platforms and tools using AI-assisted development and research.
A successful candidate will be someone who can take a relatively open-ended question such as "How is this validator performing?" , "How does this blockchain network work?" , or "Should we evaluate this technology provider?" and independently turn it into a structured technical investigation.
They will be comfortable using AI tools, data, APIs, documentation, and hands-on experimentation to quickly develop an informed point of view, and then communicate the findings clearly to stakeholders.