• Design, build, and optimize Machine Learning models powering origination, behavioral scoring, limit management, and early-warning systems • Leverage alternative data sources including transaction behavior, merchant data, and device intelligence to improve predictive performance • Evaluate and implement the infrastructure required to deploy, monitor, and retrain models at scale • Explore the applications of novel architectures (transformers, foundational models, etc.) for credit risk and related tasks • Collaborate with cross-functional teams to identify opportunities for data-driven insights and solutions • Work with other members of the Credit Risk team to build credit policies across the full customer lifecycle: origination, limit management, restructuring, and write-offs • A lot of autonomy and ownership: you will own at least one Machine Learning model end-to-end • Communicate findings and insights to technical and non-technical stakeholders

• Contribute to software systems used by millions of low-income Americans • Drive change through impactful data analysis and investigations • Maintain reliable data pipelines to ensure trustworthy data. • Work with product teams, starting with the marketplace team, but also potentially including the government benefits team, marketing, and growth. • Effectively communicate with team members during projects, code review, etc.

• Propose and conduct quantitative research into key user behaviors, product flows, and business trends; based on analysis and in collaboration with cross-functional partners, identify potential new opportunities and next steps for the product team • Design and analyze experiments and other tests for causal inference, in collaboration with engineers, applied scientists, and economists • Partner with product managers, engineers, etc. to help scope new features, e.g., scenario modeling for possible impact on key metrics, make recommendations on business logic of new features, etc. • Define and monitor key metrics; investigate changes in metrics and propose next steps • Develop topic area expertise, e.g., develop a deep understanding of how Thumbtack search works and interacts with other systems • Contribute to our team and company data culture through accessible data table design and maintenance • Collaborate with, mentor, and help recruit team members

• Serve as the analytics and data science thought partner to Product, Engineering, and GTM leadership—translating business questions into analytical frameworks and actionable insights • Define the vision and roadmap for how CircleCI uses data to make decisions, from product development to customer acquisition to retention • Lead a team where ~80% of the work is ad hoc analysis and deep investigation—answering the hard questions that don't fit neatly into a dashboard • Oversee ML modeling initiatives across product and GTM use cases (propensity models, churn prediction, usage forecasting, recommendations)