Job Description:We are seeking a Senior SAS/Python Model Validation and Modernization Developer to join our team. The successful candidate will support statistical model validation, algorithm analysis, and modernization efforts focused on migrating legacy SAS applications and processes to Python-based solutions. This role will work closely with analysts, statisticians, data scientists, and business stakeholders to evaluate model performance, conduct what-if analyses, validate outputs, and ensure the accuracy and reliability of mission-critical analytical systems. Candidates with prior U.S. Census Bureau experience or an active/previous federal clearance are highly preferred.
Duties/ Responsibilities - Test, validate, and analyze statistical, predictive, and analytical models.
- Evaluate model performance and assess the impact of parameter, assumption, and business-rule changes.
- Conduct scenario analysis, sensitivity testing, and what-if simulations to determine model behavior.
- Analyze algorithms, calculations, and methodologies to identify opportunities for optimization and improvement.
- Review existing SAS applications, scripts, and macros and develop migration strategies to Python.
- Convert SAS code, workflows, and analytical processes into maintainable Python solutions.
- Compare and validate SAS and Python outputs to ensure functional equivalency and accuracy.
- Develop automated testing frameworks and validation processes for migrated applications.
- Perform data analysis and investigate anomalies, inconsistencies, and unexpected model behavior.
- Create technical documentation, validation reports, migration plans, and process diagrams.
- Collaborate with business stakeholders, statisticians, developers, and project teams to implement analytical solutions.
- Support modernization initiatives and continuous improvement of analytical systems and processes.
Required Skills/Abilities- 4+ years of experience developing analytical solutions using SAS and Python.
- Strong experience with SAS Base Programming, SAS Macros, and SAS analytical workflows.
- Strong Python programming skills, including experience with Pandas, NumPy, and SQL.
- Experience testing, validating, and analyzing statistical or predictive models.
- Experience conducting model performance evaluations and impact analyses.
- Experience migrating SAS applications, scripts, or workflows to Python.
- Strong understanding of algorithms, data analysis, and quantitative methodologies.
- Excellent analytical, troubleshooting, and problem-solving skills.
- Strong communication and documentation skills.
- Ability to work independently and as part of a team.
- Creative problem-solving with a strong visual and storytelling instinct.
- Curiosity and experimentation with emerging technologies, particularly AI.
- Strategic mindset with the ability to connect content to broader campaign goals.
- Strong collaboration and communication skills.
- Ability to balance speed, quality, and innovation.
- U.S. Citizenship required.
Nice to Have Skills- Previous experience supporting the U.S. Census Bureau or other federal statistical agencies.
- Active or previously held Census Bureau suitability determination, Public Trust, Secret Clearance, or equivalent federal clearance.
- Experience with survey processing systems, demographic analysis, economic statistics, or federal statistical programs.
- Experience with machine learning frameworks such as Scikit-Learn, XGBoost, or TensorFlow.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with Git, CI/CD pipelines, and containerized environments.
- Experience with SAS Viya and modern analytics platforms.
Education and Experience:- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology, or related field.
Travel Requirement:
Clearance Requirement:- Ability to obtain a Public Trust clearance
- U.S. Citizenship required.
Salary Range: The salary range for this position represents Dynamo's good-faith estimate of the compensation expected to be offered at the time of hire. Actual compensation will be determined based on several factors, including, but not limited to, the responsibilities of the role, the candidate's experience, skills, education, work location, and internal equity.
85K-95k annually
