About this opportunity
Zantech lists this Data Scientist opportunity in arlington, Virginia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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 Required:
Certifications Preferred:
Required Security Clearance:
US Citizenship and the ability to obtain and maintain an active Secret or higher clearance, per contract requirements.
Outstanding Performance…Always!
Our corporate motto represents our commitment to build long-term relationships with both our clients and our employees by providing the highest quality service in everything we do. We strive for excellence for our clients and for each other. We embrace the opportunity to hire individuals with new talents and fresh perspectives.
Zantech offers competitive compensation, strong benefits, and a vacation package, as well as a fast-paced and exciting work environment.
competitive compensation
strong benefits
vacation package
Come join our team!
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Worksite address
arlington, VA, 22201, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.