Description

Key Responsibilities
Analyse and interpret existing SAS programs, including DATA steps, PROC SQL, and common analytical procedures
Translate SAS-based analytics and transformations into Python using pandas, numpy, and SQL while preserving business logic and output accuracy
Partner with Business Informatics stakeholders to understand reporting intent, metrics, and downstream usage
Validate converted logic by reconciling outputs, row counts, and aggregations between SAS and Python
Improve existing analytics pipelines by simplifying logic, increasing transparency, and reducing technical debt
Collaborate with technology and data platform teams to ensure Python solutions align with enterprise standards
Document business logic, assumptions, and data transformations for long-term maintainability

Required Qualifications
Strong experience with Python for data analysis including pandas, numpy, and SQL integration
Working knowledge of SAS with the ability to confidently read and interpret existing SAS code
Experience translating or modernizing legacy analytics or reporting logic
Solid understanding of analytics concepts such as aggregations, joins, time-based logic, and derived metrics
Ability to work closely with business users and translate analytical requirements into technical solutions
Experience validating analytical outputs and ensuring data accuracy

Preferred Qualifications
Experience in healthcare, payer, or regulated data environments
Familiarity with SAS macros and common PROC workflows
Exposure to cloud-based analytics platforms or modern data stacks
Experience supporting Business Intelligence, reporting, or informatics teams
Background in analytics engineering or data transformation roles

Key Skills

Education

Bachelor's degree