Data Scientist

About Us

Circle (NYSE: CRCL) is one of the world's leading internet financial platform companies, building the foundation of a more open, global economy through digital assets, payment applications, and programmable blockchain infrastructure. Circle's platform includes the world's largest regulated stablecoin network anchored by USDC, Circle Payments Network for global money movement, and Arc, an enterprise-grade blockchain designed to become the Economic OS for the internet.

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale financial innovation.

Circle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values:
High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.

As a Staff Data Scientist at Circle, you will partner closely with product, payments, and business leaders to transform data into strategic insights that drive decision-making and product innovation. You will leverage advanced analytics, experimentation, and quantitative methods to better understand customer behavior, product performance, and the evolving payments ecosystem. As a staff individual contributor and trusted subject matter expert, you will influence product strategy, identify new business opportunities, and help shape the future of Circle's payments products.

You will build scalable data solutions, lead complex analytical initiatives, and provide thought leadership that enables the business to make better decisions through data. This role is ideal for someone who is deeply curious, thrives in ambiguity, enjoys solving complex business problems, and is motivated by creating measurable impact at scale.

• Partner with the Payments team to design and develop foundational datasets, metrics, and analytical frameworks that support product strategy and business decision-making.
• Analyze customer behavior, product adoption, and transaction activity to generate actionable insights that improve payment experiences and drive business growth.
• Research onchain payments ecosystems, blockchain transaction data, and competitive payment solutions to inform product development and market positioning.
• Lead strategic analyses that identify new opportunities for product innovation, operational efficiency, and revenue growth.
• Build scalable reporting, dashboarding, and automation solutions using SQL, Python, and business intelligence tools to increase organizational leverage.
• Communicate analytical findings through compelling visualizations and data storytelling tailored to technical and non-technical stakeholders, including senior leadership.
• Influence product and business strategy by partnering cross-functionally with Product, Engineering, Operations, and Business leaders to drive data-informed decision-making.

• Multistakeholder - You demonstrate dedication and commitment to our customers, shareholders, employees, families, and local communities.
• Mindful - You are respectful, actively listen, and pay close attention to detail.
• Driven by Excellence - You relentlessly pursue excellence and are passionate about delivering exceptional outcomes for customers and the business.
• High Integrity - You value open and honest communication and hold yourself to the highest ethical standards.
• Future Forward - You embrace innovation and help drive the evolution of money through transformative technology.

• 10+ years of experience in Data Science, Analytics, Economics, Statistics, or a related quantitative field.
• Advanced proficiency in SQL and at least one programming language such as Python or R.
• Deep expertise in statistical modeling, experimentation, causal inference, and quantitative methods.
• Proven track record of independently leading large-scale analytical and data science initiatives from ambiguous problem statements to…