On-Site Data Scientist & AI/ML Lead – Arlington

Zantech; Arlington (VA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Strong benefits

Vacation package

Job summary

Zantech is seeking a talented Data Scientist to contribute to an On-Site project in Arlington, VA. The role involves leading data acquisition, analytics, and governance, and deploying AI/ML models to support workforce, logistics, and operations for leadership.

The candidate will design predictive, prescriptive, and descriptive models, apply NLP and network/bibliometric analyses to S&T portfolio data, and ensure outputs meet Responsible AI governance with security controls.

Qualifications

• Master's degree in a relevant field plus 10+ years of experience.
• 10+ years of data science experience including statistical analysis and ML/AI development.
• 10 years in data wrangling and pipeline development with NLP or bibliometric analysis.
• Experience with data visualization tools and communicating findings to stakeholders.

Responsibilities

• Design, develop, and deploy predictive, prescriptive, descriptive, and cognitive AI/ML models and dashboards with stakeholders.
• Apply NLP, network analysis, and bibliometric analysis to S&T portfolio data.
• Support MLOps lifecycle: model registry, drift monitoring, and automated retraining triggers.
• Ensure AI outputs comply with Responsible AI governance and security controls.
• Provide onboarding and training to build a data-literate workforce.

Skills

Statistical analysis

Python

R

SQL

ML/AI modeling

MLOps

NLP

Network analysis

Bibliometrics

Data visualization

Stakeholder communication

Education

Master's degree in Computer Science or Engineering

PhD in Data Science or related field

BA/BS with 12+ years experience accepted

Cloud ML/AI platform certification (AWS/Azure)

Tools

Tableau

Power BI

Matplotlib

Job description

Zantech is seeking a talented Data Scientist to contribute to an On-Site project in Arlington, VA. The role involves leading data acquisition, analytics, and governance, and deploying AI/ML models to support workforce, logistics, and operations for leadership.

The candidate will design predictive, prescriptive, and descriptive models, apply NLP and network/bibliometric analyses to S&T portfolio data, and ensure outputs meet Responsible AI governance with security controls.