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Join Circle as a Staff Data Scientist to transform data into strategic insights for payments innovation. Leverage advanced analytics and partner with cross-functional teams to drive data-informed decision-making.
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, expanding into strong jurisdictions. Speed and efficiency are motivators, and employees live by values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. The company offers a flexible work environment where new ideas are encouraged and everyone is a stakeholder.
As a Staff Data Scientist, you will:
- Partner closely with product, payments, and business leaders to transform data into strategic insights.
- Leverage advanced analytics, experimentation, and quantitative methods to understand customer behavior and product performance.
- Build scalable data solutions and lead complex analytical initiatives.
- Analyze customer behavior, product adoption, and transaction activity to generate actionable insights.
- Research onchain payments ecosystems and competitive payment solutions.
- Build scalable reporting, dashboarding, and automation solutions using SQL, Python, and business intelligence tools.
- Communicate analytical findings through compelling visualizations and data storytelling.
Qualifications:
- 10+ years of experience in Data Science, Analytics, Economics, Statistics, or a related quantitative field.
- Advanced proficiency in SQL, proficiency in 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.
- Strong experience influencing product strategy and business decisions through data-driven recommendations.
- Experience building scalable data products and analytical frameworks.
- Excellent analytical and problem-solving skills with strong attention to detail and data quality.
- Deep experience working with payments products, payment networks, fintech, or financial services platforms.
- Experience analyzing blockchain datasets and onchain transaction activity.
The company offers:
- A flexible work environment where new ideas are encouraged.
- Opportunities to influence product strategy and shape the future of payments products.