Data Scientist

Zantech•Arlington, VA

8d•Onsite

About The Position

Zantech is seeking a Data Scientist for an On-Site role in Arlington, VA, to support a Technical Infrastructure and Platform Support project. The Data Scientist will be the technical lead for Data Acquisition, Analytics, and Governance Services (Task 3) and will also focus on Cybersecurity and Information Assurance, ensuring Responsible AI / AI TRiSM and RLS/CLS-compliant model outputs. This role involves owning the strategy, design, and deployment of advanced analytical and AI/ML models, extracting and analyzing complex data to provide actionable insights for workforce, logistics, and operational decision-making.

Requirements

Ten (10)+ years developing and deploying analytical models to address S&T or business requirements within a DoW organization
10 years in data science (statistical analysis, predictive modeling, machine learning, algorithm development in Python, R, and SQL)
10 years in data wrangling and batch/streaming pipeline development, integrating structured and unstructured sources; experience on at least 2 distinct projects applying NLP, network analysis, or bibliometric analysis to S&T portfolio data
10 years using data visualization tools (Tableau, Power BI, matplotlib)
5 years with big data and cloud-based analytics platforms
5 years applying operational analytics to workforce, logistics, or readiness missions
Statistical analysis and predictive/prescriptive/descriptive/cognitive modeling
Python, R, SQL; ML/AI model development and MLOps lifecycle management
Natural Language Processing (NLP), network analysis, and bibliometric analysis of S&T data
Data visualization and stakeholder communication of analytical findings
Federal data governance and security frameworks (NIST SP 800-53, FISMA, DoD RMF)
Master's degree in computer science, engineering, or a related discipline, and 10+ years of experience
BA/BS with 12+ years of experience is an accepted substitute
US Citizenship and the ability to obtain and maintain an active Secret or higher clearance, per contract requirements.

Nice To Haves

Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field
Cloud ML/AI platform certification (e.g., AWS Certified Machine Learning - Specialty, Microsoft Certified: Azure AI Engineer Associate)

Responsibilities

Design, develop, and deploy predictive, prescriptive, descriptive, and cognitive AI/ML models and dashboards in collaboration with stakeholders
Apply NLP, network analysis, and bibliometric analysis to S&T portfolio data
Support automated MLOps lifecycle management, including model registry, drift monitoring, and automated retraining triggers
Ensure AI/ML outputs comply with Responsible AI (RAI) governance and inherit Row-Level/Column-Level Security controls
Provide onboarding, training, and ongoing support to build a data-literate workforce