
Worked on the PolicyEngine/policyengine-us repository to enhance state tax-credit accuracy and reliability, focusing on complex scenarios involving negative income and AGI. Addressed twelve bugs and delivered four new features by refining tax calculation logic, updating eligibility checks, and restructuring data models to prevent phantom refunds across multiple states. Leveraged Python, YAML, and automation to improve backend maintainability, strengthen integration and unit testing, and ensure policy compliance. Updated dependencies and documentation, streamlined changelog entries, and improved CI reliability. The work demonstrated depth in backend development, data structuring, and software testing, resulting in more robust and policy-compliant tax credit calculations.
December 2025: Delivered extensive state tax-credit accuracy improvements, strengthened test coverage, and refreshed dependencies in PolicyEngine/policyengine-us. Focus was on handling negative income/AGI scenarios, enforcing correct eligibility, and eliminating phantom refunds across multiple states, while also improving maintainability and CI reliability.
December 2025: Delivered extensive state tax-credit accuracy improvements, strengthened test coverage, and refreshed dependencies in PolicyEngine/policyengine-us. Focus was on handling negative income/AGI scenarios, enforcing correct eligibility, and eliminating phantom refunds across multiple states, while also improving maintainability and CI reliability.

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