Zantech is looking for a talented
Data Scientist to contribute to the success of our upcoming Technical Infrastructure and Platform Support project for an On-Site role based out of Arlington, VA.
The
Data Scientist will play a crucial role in providing:
- Data Acquisition, Analytics, and Governance Services (technical lead for all Task 3 work)
- Cybersecurity and Information Assurance (Responsible AI / AI TRiSM, RLS/CLS-compliant model outputs)
The
Data Scientist serves as the technical lead, owning the strategy, design, and deployment of advanced analytical and AI/ML models. Extracts, transforms, and analyzes complex, multi-source data sets to generate actionable insight that informs workforce, logistics, and operational decision-making for leadership.
Responsibilities include, but will not be limited to:- 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
Required Experience or Knowledge of the following technologies/functions:- 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.
- Skills Required:
- 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)
Required Education/Certifications:- Education Required:
- 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,
- Education Preferred:
- Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field
- Not specified
- Cloud ML/AI platform certification (e.g., AWS Certified Machine Learning - Specialty, Microsoft Certified: Azure AI Engineer Associate)
- Certifications Preferred:
Required Security Clearance:- US Citizenship and the ability to obtain and maintain an active Secret or higher clearance, per contract requirements.
