Senior SAS/Python Programmer

Econometrica, Inc.; Bethesda (MD); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work option

Job summary

Econometrica, Inc. seeks a Senior Programmer to lead AI-assisted modernization of legacy SAS code into Python and SQL in cloud environments. The role blends hands-on coding with design of reliable, auditable conversion workflows.

You will work with statisticians, data engineers, and clients to validate outputs, maintain documentation, and mentor junior programmers in modern analytics practices.

Qualifications

• Five or more years of hands-on SAS data analytics and reporting.
• Three or more years of hands-on Python data manipulation with Pandas.
• Three or more years of hands-on experience in a modern cloud environment (Azure, AWS, or GCP).
• Two or more years of hands-on experience in SQL.
• Ability to independently lead high-complexity programming tasks and perform QA.

Responsibilities

• Lead AI-assisted conversion of large SAS codebases to Python/SQL in cloud environments.
• Design and implement LLM-based conversion workflows and validation harnesses.
• Refactor generated code into production-quality pipelines in Azure or AWS.
• Identify data quality issues and provide remediation recommendations.
• Collaborate with data engineers, data scientists, and clients to document methods and validation.

Skills

SAS

Python

SQL

Cloud platforms

Git

Education

Master's or PhD in data science / computer science / mathematics

Tools

Pandas

Spark/PySpark

Git

Cloud environments

Job description

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Job Title

Senior SAS/Python Programmer

Job Type

Full-time

Location

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

Travel

Job Description

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 years of hands-on experience conducting advanced data analysis in SQL.
• Ability to independently investigate and lead to completion programming tasks of high complexity, and to independently conduct quality assurance and troubleshoot coding issues.
• Ability to work effectively in a multidisciplinary team setting and to develop effective relationships with clients, consultants, and contractors.
• Ability to obtain and maintain public trust security clearance.

Desired Skills and Experience:

• SAS Base and Advanced certifications.
• Certifications in cloud architecture, data engineering, or related disciplines.
• Demonstrated experience converting, refactoring, or re-platforming legacy analytic code, with a documented approach to validating that modernized outputs match legacy results.
• Experience with version control (Git) and collaborative development workflows, including code review and documentation.
• Experience with distributed processing frameworks (e.g., Spark/PySpark) for large-scale data transformation.

Additional requirements for the position could involve occasional travel relevant to the responsibilities noted above.

Education

Master's or doctorate-level degree in data science, computer science, mathematics, or a related field; OR ten (10) years of applied work experience in one of the same fields.

• Being part of a dynamic research group that continues to grow.
• Company-sponsored healthcare plan and optional vision/dental coverage.
• Excellent training and development opportunities.
• 401(k) program.
• Organized social activities.

This position is remote, though candidates may choose to work in Econometrica's office if they are local.

The office is located at a Metro stop in beautiful downtown Bethesda, MD, within walking distance of great restaurants and local fare. We have a typical office setting with a quiet-to-moderate noise level.

Physical Requirements

The physical requirements are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The above job description is not intended to be an all-inclusive list of duties and standards of the position. Other instructions and related duties may be assigned by the employee's supervisor.

Econometrica, Inc., is an Equal Opportunity Employer (EOE), and we seek to create an inclusive workplace that embraces diverse backgrounds, life experiences, and perspectives.