Analytics Modernization Lead: SAS to Open-Source

Guidehouse Digital, LLC; Beavercreek (OH); On-site; USD 92,000 - 153,000; Full time

Benefits offered by this job

Medical Insurance

Dental & Vision Insurance

Paid Holidays

401(k)

Job summary

Guidehouse is seeking an Analytics Modernization Lead to drive modernization of analytic workflows by adopting open-source technologies and modern statistical computing. You will oversee SAS-to-R/Python migrations, validation, and governance across public health data environments.

You will collaborate with biostatisticians, epidemiologists, and data scientists to ensure scientific integrity, reproducibility, and operational continuity while promoting CI/CD and scalable analytics platforms.

Qualifications

• 8+ years in analytics modernization, software development, or related field.
• Experience migrating SAS-based analytics to open-source platforms.
• Experience designing validation and reproducibility frameworks for analytics.

Responsibilities

• Lead analytics modernization initiatives and roadmaps across surveillance, research, and data science.
• Migrate SAS programs to R/Python with validation to preserve analytical intent and output.
• Develop and enforce validation, regression testing, and reporting standards.
• Mentor teams in modern software development practices and governance.

Skills

SAS-to-R/Python migration

Statistical programming

CI/CD

Version control (Git)

Data governance & validation

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Statistics, or related field

Master's degree preferred

Tools

Databricks

Azure DevOps

GitHub

Docker/Kubernetes

Palantir Foundry

Job description

Guidehouse is seeking an Analytics Modernization Lead to drive modernization of analytic workflows by adopting open-source technologies and modern statistical computing. You will oversee SAS-to-R/Python migrations, validation, and governance across public health data environments.

You will collaborate with biostatisticians, epidemiologists, and data scientists to ensure scientific integrity, reproducibility, and operational continuity while promoting CI/CD and scalable analytics platforms.