SAS to Python / R Migration Architect

The SAS to Python/R Migration Architect is responsible for end-to-end strategy, design, and governance of large-scale analytical and statistical code migrations from SAS to modern open-source ecosystems (Python and R). This role focuses on ** assessment, architecture, standards, risk management, and validation **, working closely with stakeholders and development teams to ensure accuracy, performance, and regulatory fidelity.

This is a **hands-on technical leadership role **, not just documentation or oversight.

Key Responsibilities

• Lead enterprise-scale migrations from SAS (Base SAS, PROC SQL, STAT, ETS, MACRO, etc.) to Python and/or R

• Perform **detailed SAS estate assessments **, including:

  • Code inventory and dependency mapping
  • Macro complexity analysis
  • Data access patterns (SAS datasets, DBs, flat files)
  • Statistical method equivalency analysis

• Define target-state architecture for Python/R analytics platforms (libraries, frameworks, environments)

• Establish **migration patterns and standards **, including:

  • SAS PROC → Python/R library mappings
  • Macro-to-function translation strategies
  • Reusable templates and shared components

• Design validation and reconciliation frameworks to ensure:

  • Statistical equivalence
  • Numeric tolerances
  • Regulatory and audit compliance

• Guide performance optimization strategies for large datasets

• Identify **automation opportunities **(code scanners, translators, test harnesses)

• Lead technical reviews and approve migrated code

• Mentor developers and review complex conversions

• Communicate migration risks, tradeoffs, and timelines to leadership

Requirements

• 8+ years of advanced analytics or statistical programming experience

• 5+ years hands-on SAS development (Base SAS, PROC SQL, MACRO, STAT)

• Proven experience architecting or leading SAS → Python and/or R migrations

• Deep expertise in:

  • Python (NumPy, Pandas, SciPy, statsmodels, scikit-learn)
  • and/or R (tidyverse, data.table, caret, survival, forecast)

• Strong understanding of statistical methods parity between SAS and open-source tools

• Experience with data platforms (SQL databases, cloud storage, data lakes)

• Familiarity with CI/CD, version control, and testing frameworks for analytics code

Nice to Have

• Experience in regulated environments (government, healthcare, finance)
• Prior work modernizing legacy analytics platforms
• Exposure to cloud analytics stacks (AWS, Azure, GCP)
• Experience designing automated validation frameworks

Benefits

• 401(k)
• 401(k) matching
• Dental insurance
• Flexible spending account
• Health insurance
• Life insurance
• Paid time off
• Professional development assistance
• Referral program
• Tuition reimbursement
• Vision insurance