Senior Data Scientist — ML & Data Strategy Lead

US Headquarters, NASA; Huntsville (AL); On-site; USD 120,000 - 165,000; Full time

Job summary

NASA Headquarters in Huntsville is seeking a Senior Data Scientist to serve as a technical authority guiding agency data and analytic systems. You will lead the design and deployment of advanced statistical and machine learning models, establish standards for data quality and model validation, and architect analytic environments to support mission priorities.

The role requires experience with data pipelines, MLOps practices, model deployment, monitoring, and governance across environments, and

Qualifications

• Leading the design and deployment of statistical or machine learning models and enterprise data pipelines that support mission or program decisions.
• Establishing organization-wide standards for data quality, model validation, and technical documentation and overseeing adherence to those standards.
• Developing and implementing machine learning operations practices, including model deployment, monitoring, and governance across multiple environments.

Responsibilities

• Leading the design and deployment of statistical or machine learning models and enterprise data pipelines that support mission or program decisions.
• Establishing organization-wide standards for data quality, model validation, and technical documentation and overseeing adherence to those standards.
• Developing and implementing machine learning operations practices, including model deployment, monitoring, and governance across multiple environments.

Skills

Leadership in data science

Statistical modeling

ML model deployment

Data quality standards

Model validation

Analytics strategy

Job description

NASA Headquarters in Huntsville is seeking a Senior Data Scientist to serve as a technical authority guiding agency data and analytic systems. You will lead the design and deployment of advanced statistical and machine learning models, establish standards for data quality and model validation, and architect analytic environments to support mission priorities.

The role requires experience with data pipelines, MLOps practices, model deployment, monitoring, and governance across environments, and