Data Scientist (TS/SCI)

Vantor•Herndon, VA

1d•$140,000 - $200,000•Onsite

About The Position

Vantor is seeking an experienced Data Scientist to support the development, implementation, and operationalization of advanced analytics capabilities for a large-scale U.S. Government data analytics platform. The role applies statistical analysis, machine learning, predictive modeling, and other analytical techniques to derive insights from large, complex, and diverse datasets in support of mission-critical government requirements. The Data Scientist works with data engineers, software developers, analysts, and government stakeholders to translate operational and mission needs into analytical solutions. The position includes developing and evaluating models, identifying patterns and trends, designing experiments, and integrating data science capabilities into scalable, production-oriented analytics workflows. The role requires an active TS/SCI U.S. Government security clearance, U.S. citizenship, and willingness to obtain a CI polygraph. Work is onsite at least 90% of the time, or as needs dictate, in Herndon, Virginia, or Westminster, Colorado.

Requirements

U.S. citizenship and an active TS/SCI clearance; willingness to obtain a CI polygraph.
Bachelor's degree in data science, computer science, statistics, applied mathematics, or a related quantitative discipline, plus 8 or more years of total professional experience in a technical support role.
Demonstrated experience in data science, advanced analytics, statistical modeling, machine learning, or a related technical discipline.
Strong proficiency in Python, SQL, and Elastic, including experience with Elasticsearch and analytical computing libraries such as Pandas, NumPy, SciPy, and Scikit-learn.
Demonstrated experience developing, validating, and applying statistical models, machine learning algorithms, and predictive analytics techniques to large and complex datasets.
Willingness to work onsite at least 90% of the time or as needs dictate in Herndon, Virginia, or Westminster, Colorado.

Nice To Haves

Experience with advanced machine learning techniques, such as deep learning, natural language processing (NLP), large language models (LLMs), anomaly detection, classification, or clustering.
Experience with big data technologies and distributed computing frameworks, such as Apache Spark, Hadoop, or Kafka.
Experience with machine learning frameworks, such as TensorFlow, PyTorch, or XGBoost.
Experience with cloud-based analytics and machine learning services, such as AWS, Microsoft Azure, or Google Cloud Platform.
Experience with MLOps, including model deployment, monitoring, experimentation, and lifecycle management.
Experience with data visualization and reporting tools, such as Tableau, Kibana, Power BI, or Plotly.
Experience with geospatial, graph, or time-series analytics.
Experience with responsible AI, explainable AI (XAI), model governance, and evaluation of model bias, robustness, or reliability.
Experience in government, defense, intelligence, or other regulated environments.

Responsibilities

Design, develop, implement, and evaluate statistical models, machine learning algorithms, and predictive analytics solutions for complex analytical and mission requirements.
Analyze large, complex, and diverse datasets to identify patterns, trends, relationships, anomalies, and actionable insights using appropriate statistical and computational techniques.
Develop, train, validate, and optimize machine learning models, assessing performance, accuracy, scalability, and operational suitability.
Collaborate with data engineers and software developers to operationalize analytical models and integrate data science capabilities into the broader analytics platform.
Translate mission and business requirements into analytical approaches.
Communicate findings, methodologies, and recommendations to technical teams, government stakeholders, and senior leadership.