Data Scientist I: Mission Analytics & Visualization

VTG Defense; Chantilly (VA); On-site; USD 105,000 - 215,000; Full time

Job summary

VTG Defense in Chantilly, VA is seeking a Data Scientist I to support government and program teams by performing data analysis, visualization, and reporting to inform mission and business decisions under supervision.

You will gather and clean data, perform exploratory analysis, develop simple dashboards, document methodologies, and collaborate with data engineers, analysts, and stakeholders in a fast-paced environment.

Qualifications

• TS/SCI with Poly is required.
• 1-4 years of experience supporting data analysis or analytics projects.
• Familiarity with Python, R, SQL or similar analytical tools.
• Familiarity with Jupyter, Tableau, Power BI or similar.
• Basic understanding of statistics and data visualization.
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science or related field.

Responsibilities

• Support collection, cleaning and preparation of structured and semistructured data.
• Assist with exploratory data analysis and basic statistical assessments.
• Develop simple dashboards, visualizations and analytical summaries.
• Support documentation of data sources, assumptions and methodologies.
• Participate in analytic working groups and technical discussions.
• Assist with maintaining data pipelines, scripts and analysis artifacts.
• Support coordination between data engineers, analysts, and mission stakeholders.

Skills

Analytical thinking

Communication skills

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field

Tools

Python

R

SQL

Jupyter

Tableau

Power BI

Job description

VTG Defense in Chantilly, VA is seeking a Data Scientist I to support government and program teams by performing data analysis, visualization, and reporting to inform mission and business decisions under supervision.

You will gather and clean data, perform exploratory analysis, develop simple dashboards, document methodologies, and collaborate with data engineers, analysts, and stakeholders in a fast-paced environment.