Remote Data Architect: AI & Data Quality Lead

ASRC Federal; Washington, Northern (District of Columbia, KY); Hybrid; USD 150,000 - 190,000; Full time

Job summary

ASRC Federal is seeking a remote Data Architect to lead enterprise data architecture for the ICE LESA program. The role focuses on data standards, scalable models, governance, and interoperability to enable reliable analytics and modernization efforts.

The candidate will design data remediation approaches, develop AI/ML models, and collaborate with stakeholders to align data strategies with operational needs and security requirements.

Qualifications

• Bachelor’s degree in data science, statistics, computer science, engineering, mathematics or related field.
• At least eight years of experience in data science or advanced analytics in operational settings.
• Proficiency with SQL, Python, R, and Databricks; strong communication to explain concepts.

Responsibilities

• Lead design, development, validation, and documentation of data remediation approaches.
• Ensure data approaches comply with DHS/ICE policies and LESA standards.
• Develop AI/ML models to detect and remediate data quality issues.
• Oversee integration of AI-driven models, automation scripts, dashboards, and tools.
• Collaborate with stakeholders to identify data quality issues and corrective actions.
• Facilitate user training and knowledge transfer on analytics processes.

Skills

SQL

Python

R

Databricks

AI/ML techniques

Education

Bachelor’s degree in data science, statistics, computer science, engineering, or mathematics

Advanced degree preferred (MS/PhD)

Tools

Data quality tools

Analytical dashboards

Job description

ASRC Federal is seeking a remote Data Architect to lead enterprise data architecture for the ICE LESA program. The role focuses on data standards, scalable models, governance, and interoperability to enable reliable analytics and modernization efforts.

The candidate will design data remediation approaches, develop AI/ML models, and collaborate with stakeholders to align data strategies with operational needs and security requirements.