Senior SAS​/Python Programmer

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Senior SAS/Python Programmer

Full-time

Bethesda Office - Bethesda, MD 20814 US (Primary)
Remote (Virtual) - US - US

About Econometrica, Inc.

Econometrica, Inc., is a research and management organization committed to providing high-quality, cost-effective economic and analytical services for clients in the private and public sectors. Since its founding in 1998, Econometrica has been involved in complex, high-profile contracts for numerous Federal departments and agencies in the healthcare, education, transportation, energy, housing, and finance sectors. Econometrica specializes in research, econometric, analytical, and technical support for our clients, with an emphasis on data science, data analytics, statistics, economic analyses, and program implementation and evaluation services.

The Opportunity

Econometrica is seeking a Senior Programmer to lead the AI-assisted conversion of large legacy SAS codebases into modern SQL- and Python-based cloud computing environments. This is a hands-on engineering role for someone who is genuinely fluent in both languages: the ideal candidate can read a 3,000-line SAS macro with nested%
DOloops,PROC SQLpass-through, and multi-level formats and understand what the equivalent, maintainable Python or SQL implementation should look like.

The selected candidate will use large language models (LLMs) and generative AI tooling as a force multiplier — not as a black box. A central responsibility of this role is designing the workflow that makes AI-assisted conversion trustworthy: decomposing legacy code into translatable units, engineering prompts and context that produce correct output, and building the automated validation harnesses that prove the converted code reproduces the original results to the row and to the decimal.

The candidate will work alongside a multidisciplinary team of statistical programmers, data engineers, data scientists, and client stakeholders, and will help establish the conversion patterns, standards, and documentation that subsequent modernization projects reuse.

Tasks may include the following:

• Assessing and inventorying existing SAS code bases—including DATA steps, PROC SQL, macros, arrays, formats, and complex conditional logic—to determine business logic, data lineage, dependencies, and modernization priorities.
• Designing, prompting, and iterating on LLM-based conversion workflows to re-engineer SAS programs for Python- and SQL-based cloud environments while avoiding literal "SAS-in-Python" anti-patterns and applying appropriate performance optimizations.
• Building and running equivalence-testing harnesses that compare legacy SAS output against converted output at scale — row counts, key-level joins, column-by-column value comparison with defined numeric tolerances, distributional checks, and edge-case handling — and documenting every accepted discrepancy with its justification.
• Refactoring machine-generated code into production-quality, modular pipelines in modern cloud environments, which may include Azure or AWS, and coordinating with the Data Engineering team on orchestration, scheduling, and deployment.
• Identifying data quality issues surfaced during conversion and developing recommendations on how to resolve them to ensure data completeness, consistency, and accuracy for clients' analytical products.
• Documenting conversion methodology, mapping logic, validation evidence, and residual risk in a form suitable for client acceptance, audit, and recordkeeping requirements — and preparing plain-language summaries for nontechnical audiences.
• Mentoring junior SAS and Python programmers on modernization techniques and on the responsible, verified use of AI coding assistants.

Education and Qualifications

Required

Skills and Experience:

• Five (5) or more years of hands-on experience using SAS for data analytics and reporting.
• Three (3) or more years of hands-on experience manipulating data in Python, with required proficiency in Pandas.
• Three (2) or more years of hands-on experience working in a modern cloud environment (Azure, AWS, or GCP).
• Two (2) or more…