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Assistant Conservation Data Science Jobs in Virginia

... end-to-end data science and data engineering workflows, from data preparation and feature ... assist with briefings or presentations to technical and non-technical stakeholders. • Support ...

On our team, you'll use your leadership skills and data science expertise to create real-world ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

On our team, you'll use your leadership skills and data science expertise to create real-world ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

Contribute to end-to-end data science and data engineering workflows, from data preparation and ... Write clear, well-structured documentation of methods, assumptions, and results; assist with ...

Provide statistical, mathematical, visualization, or coding support to assist an Intelligence ... Bachelor's degree in Data Science, Statistics, Data Analytics, or Business Analytics Nice If You ...

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Assistant Conservation Data Science information

What are the most commonly searched types of Conservation Data Science jobs in Virginia? The most popular types of Conservation Data Science jobs in Virginia are:
What cities in Virginia are hiring for Assistant Conservation Data Science jobs? Cities in Virginia with the most Assistant Conservation Data Science job openings:
Infographic showing various Assistant Conservation Data Science job openings in Virginia as of June 2026, with employment types broken down into 2% As Needed, 70% Full Time, 22% Part Time, and 6% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Data Scientist

Vantor

Reston, VA • On-site

Full-time

Posted 20 days ago


Job description

Job Summary:
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. They are seeking a Data Scientist to provide critical analytic insights to government stakeholders, developing accurate, scalable data solutions that enable timely decision-making. The role involves automating data workflows, analyzing datasets, developing predictive models, and collaborating with various teams.
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.
Qualifications:
Required:
• 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:
• 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.
Company:
A spatial intelligence firm. Founded in 2025, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.