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# Full Stack Data Scientist (Multiple roles/skill levels)

- **Company:** Kforce Inc.
- **Location:** Arlington, DC, United States
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Data Analysis, Big Data, Cloud Computing Security, Cloud Engineering, Continuous Integration, Data Architecture, Data Governance, Data Infrastructure, Data Integration, Database Design, Database Storage Structures, DevOps, Web Development, Distributed Computing Environment, Design of User Interfaces, Python (Programming Language), Performance Tuning, Standard Sql, Software Construction, Software Engineering, SQL Databases, Web Applications, Web Application Frameworks, Enterprise Data Management, Data Ingestion, ReactJS, Flask (Web Framework), Git, Containerization, Data Analytics, Machine Learning Operations, Data Pipelines, Docker, Databricks
- **Published:** August 5, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9076001/full-stack-data-scientist-multiple-rolesskill-levels

## About the Role

Junior Data Scientist (0-3 Years)
Experience with Python development and data analysis.
Foundational SQL skills.
Understanding of data modeling concepts and analytics workflows.
Exposure to web application development or software engineering principles.
Ability to learn and work within secure, mission-focused environments.

Senior Data Scientist (3-8 Years)
Strong experience developing data science and analytics applications.
Advanced Python programming experience.
Strong SQL and database design expertise.
Experience building data-driven web applications using Dash, Flask, React, or similar technologies.
Experience with Databricks and distributed data processing environments.
Knowledge of containerization and DevOps methodologies.
Ability to build complex data models and analytical solutions.

Lead Data Scientist (5-10 Years)
Proven experience leading data science and software development efforts.
Expertise designing enterprise-scale analytical applications and architectures.
Strong experience building and deploying full-stack data products.
Experience mentoring technical teams and driving engineering best practices.
Deep understanding of modern software engineering, CI/CD, DevOps, and cloud-native deployments.
Ability to engage directly with stakeholders and translate business requirements into technical solutions., Experience supporting federal, defense, or intelligence community programs.
Experience with Advana or Warfighter Data Platform (WDP).
Hands-on Databricks experience and relevant certifications.
Experience with machine learning workflows and model deployment.
JavaScript development experience.
Experience with Docker and Kubernetes.
Knowledge of modern data architecture and enterprise analytics platforms.
Familiarity with secure cloud environments and large-scale datasets.

Technical Environment
Python
SQL
Databricks
Dash
Flask
React
JavaScript
Docker
Kubernetes
Git
CI/CD Pipelines
DevOps
Enterprise Data Platforms

## Description

This role spans the complete data lifecycle, from data ingestion and modeling to application development, deployment, and user-facing visualization solutions. Successful candidates will have experience working with modern data platforms, software engineering best practices, and cloud-native technologies., Design, develop, and deploy full-stack data applications supporting mission and business objectives.
Build advanced data models, machine learning workflows, and analytical solutions using Python and SQL.
Develop scalable web-based applications using modern frameworks and technologies.
Architect and optimize data pipelines, database structures, and data integration processes.
Create intuitive dashboards, user interfaces, and visualizations that enable data-driven decision-making.
Develop backend APIs and services that support enterprise analytics applications.
Implement CI/CD pipelines and DevOps processes to streamline development and deployment.
Deploy and maintain containerized applications using Docker and Kubernetes.
Collaborate with engineers, analysts, stakeholders, and leadership to translate requirements into technical solutions.
Support data governance, system performance optimization, and software engineering best practices.


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