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# Data Scientist (TS/SCI)

- **Company:** Vantor Inc.
- **Location:** Westminster, CO, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Data Integration, Distributed Computing Environment, Elasticsearch, Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Power BI, Tensorflow, SciPy, SQL Databases, Tableau (Software), Explainable AI (XAI), Google Cloud, Pytorch, Large Language Models, Apache Spark, Deep Learning, Pandas, Scikit Learn, Information Technology, Data Analytics, Xgboost, Plotly, Apache Kafka, Data Management, Machine Learning Operations, Kibana
- **Published:** November 4, 2026
- **Apply:** https://diversityjobs.com/career/18829176/Data-Scientist-Ts-Sci-Colorado-Westminster

## About the Role

* Must be a U.S. Citizen with an active TS/SCI clearance (With willingness to obtain a CI poly)

 * Bachelor's degree in data science, computer science, statistics, applied mathematics, or related quantitative discipline with 8+ 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 with experience using 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% or as needs dictate in either Herndon, VA or Westminster, CO., * Advanced machine learning techniques, such as deep learning, natural language processing (NLP), large language models (LLMs), anomaly detection, classification, or clustering
 * Big data technologies and distributed computing frameworks, such as Apache Spark, Hadoop, or Kafka
 * Machine learning frameworks, such as TensorFlow, PyTorch, or XGBoost
 * Cloud-based analytics and machine learning services, such as AWS, Microsoft Azure, or Google Cloud Platform
 * MLOps, including model deployment, monitoring, experimentation, and lifecycle management
 * Data visualization and reporting tools, such as Tableau, Kibana, Power BI, or Plotly
 * Geospatial, graph, or time-series analytics
 * Responsible AI, explainable AI (XAI), model governance, and evaluation of model bias, robustness, or reliability
 * Government, defense, intelligence, or other regulated environments

#cjpost

#LI-RD

#LI-Onsite

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate's starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.

## Description

We are 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 successful candidate will apply statistical analysis, machine learning, predictive modeling, and other advanced analytical techniques to extract meaningful insights from large, complex, and diverse datasets in support of mission-critical government requirements.

The Data Scientist will work closely with data engineers, software developers, analysts, and government stakeholders to translate operational and mission needs into analytical solutions. Responsibilities will include developing and evaluating analytical models, identifying patterns and trends, designing experiments, and integrating data science capabilities into scalable, production-oriented analytics workflows., * Advanced Analytics and Modeling: Design, develop, implement, and evaluate statistical models, machine learning algorithms, and predictive analytics solutions to address complex analytical and mission requirements.

 * Data Exploration and Analysis: Analyze large, complex, and diverse datasets to identify patterns, trends, relationships, anomalies, and actionable insights using appropriate statistical and computational techniques.
 * Machine Learning and Model Development: Develop, train, validate, and optimize machine learning models; assess model performance, accuracy, scalability, and operational suitability.
 * Analytical Solution Integration: Collaborate with data engineers and software developers to operationalize analytical models and integrate data science capabilities into the broader analytics platform.
 * Analytical Leadership and Communication: Translate mission and business requirements into analytical approaches; communicate findings, methodologies, and recommendations to technical teams, government stakeholders, and senior leadership.