Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph.
5 years of professional experience in data science, analytics, or data engineering roles.
Bachelor's degree in data science, computer science, engineering, statistics, GIS, or related discipline. Degree may be substituted with an additional 2 yrs of experience.
Strong coding proficiency in Python and SQL , with experience writing production-quality, maintainable code; working knowledge of R is a plus.
Hands-on experience with data manipulation, feature engineering, machine learning libraries (e.g., scikit-learn, PyTorch , TensorFlow), and automation tools.
Experience contributing to full-cycle data projects, including data preparation, modeling, validation, and reporting.
Ability to clearly communicate technical concepts and analytical results in writing and verbally.
Familiarity with NLP and LLM concepts, including practical experience applying pre-trained models (e.g., GPT-style models) for automation, summarization, or search.
Ability to work effectively in a collaborative environment, taking direction and feedback while owning assigned technical tasks.
Preferred Qualifications: Master's degree in data science, computer science, statistics, engineering, or a related technical field.
Experience with cloud-based environments (e.g., AWS, Azure, or GCP) and scalable data processing pipelines.
Working knowledge of NLP techniques, embeddings, vector search, or retrieval-augmented generation (RAG).
Experience integrating LLMs into applications or workflows using APIs and open-source tooling.
Exposure to CI/CD, version control, testing frameworks, and software engineering best practices.
Interest in responsible AI principles, model evaluation, and risk-aware deployment of LLM-based solutions.
Additional Information
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. Vantor is a place for problem solvers, changemakers, and go-getters-where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.
To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status.
Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).
Please review the job details below.
This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI Polygraph.
This project supports a hard and deeply buried target mission set, providing critical analytic insights to government stakeholders. Success depends on the development of accurate , scalable, and mission-tailored data solutions that enable timely and informed decision-making. The work directly impacts national security objectives by transforming complex data into actionable intelligence in a highly specialized and sensitive domain.
Responsibilities: Automate and maintain data extraction, cleaning, processing, and analysis workflows using Python, SQL, and ETL tools under established best practices.
Process and analyze structured and unstructured datasets using big data or cloud-native frameworks (e.g., Spark, Hadoop, or managed cloud services).
Develop, test, and evaluate predictive models and statistical analyses to support mission-focused use cases.
Contribute to end-to-end data science and data engineering workflows, from data preparation and feature engineering through model development and results delivery, with guidance from senior team members as needed.
Write clear, well-structured documentation of methods, assumptions, and results; assist with briefings or presentations to technical and non-technical stakeholders.
Support the use of Large Language Models (LLMs) within existing systems and workflows, including:
Implementing LLM-based solutions for summarization, tagging, classification, and information retrieval.
Integrating pre-trained LLMs into pipelines to improve knowledge discovery and data accessibility.
Assisting with deployment and evaluation of internal LLM-enabled tools or assistants.
Collaborate closely with data scientists, engineers, analysts, and mission partners to refine requirements and iterate on solutions.
Maxar · Reston, VA